The survey on the computer vision works under the adverse weather conditions
| Emoji | Description |
|---|---|
| π· | Single Image |
| πΉ | Video-based |
| π°οΈ | Remote Sensing Data |
| π | Night |
| π | Benchmark |
Venue Abbreviation (click to expand)
- Conference:
| Abbreviation | Full Name |
|---|---|
| CVPR | Computer Vision and Pattern Recognition |
| ICCV | International Conference on Computer Vision |
| ECCV | European Conference on Computer Vision |
| AAAI | AAAI Conference on Artificial Intelligence |
| ICASSP | IEEE International Conference on Acoustics, Speech, and Signal Processing |
| WACV | IEEE Winter Conference on Applications of Computer Vision |
| ICAR | IEEE International Conference on Robotics and Automation |
| ACCV | Asian Conference on Computer Vision |
| ACPR | Asian Conference on Pattern Recognition |
| ISM | IEEE International Symposium on Multimedia |
| ICIP | IEEE International Conference on Image Processing |
| CVM | Computational Visual Media |
| ICTC | International Conference on Information and Communication Technology Convergence |
| ITSC | IEEE International Intelligent Transportation Systems Conference |
- Journal:
| Abbreviation | Full Name |
|---|---|
| TOG | ACM Transactions on Graphics |
| TPAMI | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| IJCV | International Journal of Computer Vision |
| TIP | IEEE Transactions on Image Processing |
| TCSVT | IEEE Transactions on Circuits and Systems for Video Technology |
| TIM | IEEE Transactions on Instrumentation and Measurement |
| TCI | IEEE Transactions on Computational Imaging |
| ARCME | Archives of Computational Methods in Engineering |
| OE | Optical Engineering |
| Opt. Express | Optics Express |
-
Low-level Vision
Β Β Β Β π«οΈ Haze removal / Fog Removal / Dehazing / Defogging
Β Β Β Β π§οΈ Rain removal / Deraining / De-raining
Β Β Β Β Β Β Β Β β Rain Streak Removal
Β Β Β Β Β Β Β Β π§ Raindrop Removal
Β Β Β Β βοΈ Snow Removal / Desnowing / De-snowing
Β Β Β Β All-in-One (AiO) Adverse Weather Removal -
High-level Vision
Β Β Β Β Object Detection
Β Β Β Β Semantic Segmentation
Β Β Β Β Object Tracking
Β Β Β Β Depth Estimation
Β Β Β Β Autonomous Driving
Β Β Β Β Scene Stylization
| Paper | Venue | Year | Data | Link | Code |
|---|---|---|---|---|---|
| A comprehensive review of computational dehazing techniques Dilbag Singh, Vijay Kumar |
ARCME | 2018 | π· | Paper | |
| A survey on all-in-one image restoration: Taxonomy, evaluation and future trends Junjun Jiang, Zengyuan Zuo, Gang Wu, Kui Jiang, Xianming Liu |
TPAMI | 2025 | π· | Paper | Code |
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| Visibility in bad weather from a single image Robby T. Tan |
CVPR | 2008 | π· | Model-based | Paper | Code |
| Benchmarking single-image dehazing and beyond Boyi Li; Wenqi Ren; Dengpan Fu; Dacheng Tao; Dan Feng; Wenjun Zeng |
TIP | 2018 | π·π | Benchmark | Paper | Code |
| Single image dehazing Raanan Fattal |
TOG | 2008 | π· | Model-based | Paper | Code |
| Enhanced pix2pix dehazing network Yanyun Qu; Yizi Chen; Jingying Huang; Yuan Xie |
CVPR | 2019 | π· | CNN | Paper | Code |
| Contrastive learning for compact single image dehazing Haiyan Wu, Yanyun Qu, Shaohui Lin, Jian Zhou, Ruizhi Qiao, Zhizhong Zhang, Yuan Xie, Lizhuang Ma |
CVPR | 2021 | π· | Contrastive Learning | Paper | Code |
| Non-local image dehazing Dana Berman, Tali Treibitz, Shai Avidan |
CVPR | 2016 | π· | Model-based | Paper | Code |
| Vision transformers for single image dehazing Yuda Song, Zhuqing He, Hui Qian, Xin Du |
TIP | 2023 | π· | Transformer | Paper | Code |
| Cycle-dehaze: Enhanced cyclegan for single image dehazing Deniz Engin, Anil Genc, Hazim Kemal Ekenel |
CVPR | 2018 | π· | GAN | Paper | Code |
| Single image dehazing by multi-scale fusion Codruta Orniana Ancuti, Cosmin Ancuti |
TIP | 2013 | π· | Fusion-based | Paper | Code |
| Dehazing using color-lines Raanan Fattal |
TOG | 2014 | π· | Model-based | Paper | Code |
| A comprehensive review on analysis and implementation of recent image dehazing methods Subhash Chand Agrawal, Anand Singh Jalal |
ARCME | 2022 | π· | Survey | Paper | |
| Single image dehazing via multi-scale convolutional neural networks Wenqi Ren, Si Liu, Hua Zhang, Jinshan Pan, Xiaochun Cao, Ming-Hsuan Yang |
ECCV | 2016 | π· | Fusion-based | Paper | Code |
| A review of remote sensing image dehazing Juping Liu, Shiju Wang, Xin Wang, Mingye Ju, Dengyin Zhang |
Sensors | 2021 | π· | Survey | Paper | Code |
| Aod-net: All-in-one dehazing network Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, Dan Feng |
ICCV | 2017 | π· | CNN | Paper | Code |
| An all-in-one network for dehazing and beyond Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, Dan Feng |
ArXiv | 2017 | π· | CNN | Paper | Code |
| An investigation of dehazing effects on image and video coding Kristofor B. Gibson, Dung T. Vo, Truong Q. Nguyen |
TIP | 2011 | πΉ | Model-based | Paper | |
| Griddehazenet: Attention-based multi-scale network for image dehazing Xiaohong Liu, Yongrui Ma, Zhihao Shi, Jun Chen |
ICCV | 2019 | π· | CNN | Paper | Code |
| Fast image dehazing method based on linear transformation Wencheng Wang, Xiaohui Yuan, Xiaojin Wu, Yunlong Liu |
2017 | π· | Model-based | Paper | ||
| Domain adaptation for image dehazing Yuanjie Shao, Lerenhan Li, Wenqi Ren, Changxin Gao, Nong Sang |
CVPR | 2020 | π· | Domain Adaptation | Paper | Code |
| Perceiving and modeling density for image dehazing Tian Ye, Yunchen Zhang, Mingchao Jiang, Liang Chen, Yun Liu, Sixiang Chen, Erkang Chen |
ECCV | 2022 | π· | CNN | Paper | Code |
| Densely connected pyramid dehazing network He Zhang, Vishal M. Patel |
CVPR | 2018 | π· | CNN | Paper | Code |
| Single remote sensing image dehazing Jiao Long, Zhenwei Shi, Wei Tang, Changshui Zhang |
2013 | π· | Model-based | Paper | Code | |
| Single image dehazing using haze-lines Dana Berman, Tali Treibitz, Shai Avidan |
TPAMI | 2018 | π· | Model-based | Paper | |
| D-hazy: A dataset to evaluate quantitatively dehazing algorithms Cosmin Ancuti, Codruta O. Ancuti, Christophe De Vleeschouwer |
ICIP | 2016 | π· | Benchmark | Paper | |
| Recent advances in image dehazing Wencheng Wang, Xiaohui Yuan |
JAS | 2017 | π· | Survey | Paper | |
| Gated fusion network for single image dehazing Wenqi Ren, Lin Ma, Jiawei Zhang, Jinshan Pan, Xiaochun Cao, Wei Liu, Ming-Hsuan Yang |
CVPR | 2018 | π· | Fusion-based | Paper | Code |
| Dehazegan: When image dehazing meets differential programming. Hongyuan Zhu, Xi Peng, Vijay Chandrasekhar, Liyuan Li, Joo-Hwee Lim |
2018 | π· | GAN | Paper | ||
| Semi-supervised image dehazing Lerenhan Li, Yunlong Dong, Wenqi Ren, Jinshan Pan, Changxin Gao, Nong Sang, Ming-Hsuan Yang |
TIP | 2019 | π· | Unsupervised | Paper | Code |
| Instant dehazing of images using polarization Y.Y. Schechner, S.G. Narasimhan, S.K. Nayar |
CVPR | 2001 | π· | Polarization | Paper | |
| Single image dehazing based on the physical model and MSRCR algorithm Jinbao Wang, Ke Lu, Jian Xue, Ning He, Ling Shao |
TCSVT | 2017 | π· | Model-based | Paper | Code |
| Trident dehazing network Jing Liu, Haiyan Wu, Yuan Xie, Yanyun Qu, Lizhuang Ma |
CVPR | 2020 | π· | CNN | Paper | Code |
| Review of dehazing techniques: challenges and future trends Abeer Ayoub, Walid El-Shafai, Fathi E. Abd El-Samie, Ehab K. I. Hamad, El-Sayed M. EL-Rabaie |
Multimed Tools Appl. | 2025 | π· | Survey | Paper | |
| Investigating haze-relevant features in a learning framework for image dehazing Ketan Tang, Jianchao Yang, Jue Wang |
CVPR | 2014 | π· | CNN | Paper | Code |
| Single image dehazing using saturation line prior Pengyang Ling, Huaian Chen, Xiao Tan, Yi Jin, Enhong Chen |
TIP | 2023 | π· | Model-based | Paper | Code |
| EENet: An effective and efficient network for single image dehazing Yuning Cui, Qiang Wang, Chaopeng Li, Wenqi Ren, Alois Knoll |
PR | 2025 | π· | CNN | Paper | Code |
| Efficient image dehazing with boundary constraint and contextual regularization Gaofeng Meng, Ying Wang, Jiangyong Duan, Shiming Xiang, Chunhong Pan |
ICCV | 2013 | π· | Model-based | Paper | Code |
| Quality evaluation of image dehazing methods using synthetic hazy images Xiongkuo Min, Guangtao Zhai, Ke Gu, Yucheng Zhu, Jiantao Zhou, Guodong Guo, Xiaokang Yang, Xinping Guan, Wenjun Zhang |
2019 | π· | Benchmark | Paper | ||
| Single image dehazing via conditional generative adversarial network Runde Li, Jinshan Pan, Zechao Li, Jinhui Tang |
CVPR | 2018 | π· | GAN | Paper | Code |
| Initial results in underwater single image dehazing N Carlevaris-Bianco, A Mohan, R M Eustice |
2010 | π· | Model-based | Paper | ||
| Frequency and spatial dual guidance for image dehazing Hu Yu, Naishan Zheng, Man Zhou, Jie Huang, Zeyu Xiao, Feng Zhao |
ECCV | 2022 | π· | Paper | Code | |
| End-to-end united video dehazing and detection Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, Dan Feng |
AAAI | 2018 | πΉ | CNN | Paper | |
| Dehazing evaluation: Real-world benchmark datasets, criteria, and baselines Shiyu Zhao, Lin Zhang, Shuaiyi Huang, Ying Shen, Shengjie Zhao |
TIP | 2020 | π· | Benchmark | Paper | Code |
| Single image dehazing using ranking convolutional neural network Yafei Song, Jia Li, Xiaogang Wang, Xiaowu Chen |
2017 | π· | CNN | Paper | ||
| Rethinking performance gains in image dehazing networks Yuda Song, Yang Zhou, Hui Qian, Xin Du |
ArXiv | 2022 | π· | CNN | Paper | Code |
| Learning deep priors for image dehazing Yang Liu, Jinshan Pan, Jimmy Ren, Zhixun Su |
ICCV | 2019 | π· | Model-based | Paper | Code |
| FAMED-Net: A fast and accurate multi-scale end-to-end dehazing network Jing Zhang, Dacheng Tao |
TIP | 2019 | π· | CNN | Paper | Code |
| A comparative study of image dehazing algorithms Anil Singh Parihar, Yash Kumar Gupta, Yash Singodia, Vibhu Singh, Kavinder Singh |
2020 | π· | Survey | Paper | ||
| Color image dehazing using the near-infrared Lex Schaul, Clement Fredembach, Sabine Susstrunk |
ICIP | 2009 | π· | Fusion-based | Paper | |
| Image dehazing using polarization effects of objects and airlight Shuai Fang, XiuShan Xia, Xing Huo, ChangWen Chen |
Opt. Express | 2014 | π· | Polarization | Paper | |
| An iterative image dehazing method with polarization Linghao Shen, Yongqiang Zhao, Qunnie Peng, Jonathan Cheung-Wai Chan, Seong G. Kong |
2018 | π· | Polarization | Paper | Code | |
| Effective single image dehazing by fusion Codruta Orniana Ancuti, Cosmin Ancuti, Philippe Bekaert |
ICIP | 2010 | π· | Fusion-based | Paper | |
| Perceptual evaluation of single image dehazing algorithms Kede Ma, Wentao Liu, Zhou Wang |
ICIP | 2015 | π· | Benchmark | Paper | |
| Curricular contrastive regularization for physics-aware single image dehazing Yu Zheng, Jiahui Zhan, Shengfeng He, Junyu Dong, Yong Du |
CVPR | 2023 | π· | Contrastive Learning | Paper | Code |
| Zero-shot image dehazing Boyun Li, Yuanbiao Gou, Jerry Zitao Liu, Hongyuan Zhu, Joey Tianyi Zhou, Xi Peng |
TIP | 2020 | π· | Unsupervised | Paper | Code |
| Light-DehazeNet: a novel lightweight CNN architecture for single image dehazing Hayat Ullah, Khan Muhammad, Muhammad Irfan, Saeed Anwar, Muhammad Sajjad, Ali Shariq Imran, Victor Hugo C. de Albuquerque |
TIP | 2021 | π· | CNN | Paper | Code |
| Image dehazing using residual-based deep CNN Jinjiang Li, Guihui Li, Hui Fan |
2018 | π· | CNN | Paper | Code | |
| A fast image dehazing algorithm using morphological reconstruction Sebastian Salazar-Colores, Eduardo Cabal-Yepez, Juan M. Ramos-Arreguin, Guillermo Botella, Luis M. Ledesma-Carrillo, Sergio Ledesma |
TIP | 2018 | π· | Model-based | Paper | |
| Efficient single image dehazing and denoising: An efficient multi-scale correlated wavelet approach Xin Liu, He Zhang, Yiu-ming Cheung, Xinge You, Yuan Yan Tang |
2017 | π· | Model-based | Paper | ||
| A review on dark channel prior based image dehazing algorithms Sungmin Lee, Seokmin Yun, Ju-Hun Nam, Chee Sun Won, Seung-Won Jung |
2016 | π· | Survey | Paper | ||
| Physics-based feature dehazing networks Jiangxin Dong, Jinshan Pan |
ECCV | 2020 | π· | CNN | Paper | |
| Deep video dehazing with semantic segmentation Wenqi Ren, Jingang Zhang, Xiangyu Xu, Lin Ma, Xiaochun Cao, Gaofeng Meng, Wei Liu |
TIP | 2018 | πΉ | CNN | Paper | |
| Hazerd: an outdoor scene dataset and benchmark for single image dehazing Yanfu Zhang, Li Ding, Gaurav Sharma |
ICIP | 2017 | π· | Benchmark | Paper | |
| U-shaped vision mamba for single image dehazing Zhuoran Zheng, Chen Wu |
ArXiv | 2024 | π· | Transformer | Paper | |
| FFA-Net: Feature fusion attention network for single image dehazing Xu Qin, Zhilin Wang, Yuanchao Bai, Xiaodong Xie, Huizhu Jia |
AAAI | 2020 | π· | CNN | Paper | |
| O-haze: a dehazing benchmark with real hazy and haze-free outdoor images Codruta O. Ancuti, Cosmin Ancuti, Radu Timofte, Christophe De Vleeschouwer |
CVPR | 2018 | π· | Benchmark | Paper | |
| Image dehazing transformer with transmission-aware 3d position embedding Chun-Le Guo, Qixin Yan, Saeed Anwar, Runmin Cong, Wenqi Ren, Chongyi Li |
CVPR | 2022 | π· | Transformer | Paper | |
| Single image dehazing based on contrast enhancement Jin-Hwan Kim, Jae-Young Sim, Chang-Su Kim |
ICASSP | 2011 | π· | Model-based | Paper | |
| RefineDNet: A weakly supervised refinement framework for single image dehazing Shiyu Zhao, Lin Zhang, Ying Shen, Yicong Zhou |
TIP | 2021 | π· | Unsupervised | Paper | |
| Underwater image enhancement by wavelength compensation and dehazing J. Y. Chiang, Ying-Ching Chen |
TIP | 2011 | π· | Fusion-based | Paper | |
| Knowledge transfer dehazing network for nonhomogeneous dehazing Haiyan Wu, Jing Liu, Yuan Xie, Yanyun Qu, Lizhuang Ma |
CVPR | 2020 | π· | CNN | Paper | |
| Near-infrared guided color image dehazing Chen Feng, Shaojie Zhuo, Xiaopeng Zhang, Liang Shen, Sabine SΓΌsstrunk |
ICIP | 2013 | π· | Fusion-based | Paper | |
| A review on intelligence dehazing and color restoration for underwater images Min Han, Zhiyu Lyu, Tie Qiu, Meiling Xu |
2018 | π· | Survey | Paper | ||
| UCL-dehaze: Toward real-world image dehazing via unsupervised contrastive learning Yongzhen Wang, Xuefeng Yan, Fu Lee Wang, Haoran Xie, Wenhan Yang, Xiao-Ping Zhang, Jing Qin, Mingqiang Wei |
TIP | 2024 | π· | Contrastive Learning | Paper | |
| Enhanced variational image dehazing Adrian Galdran, Javier Vazquez-Corral, David Pardo, Marcelo BertalmΓo |
2015 | π· | Variational | Paper | ||
| Optimized contrast enhancement for real-time image and video dehazing Jin-Hwan Kim, Won-Dong Jang, Jae-Young Sim, Chang-Su Kim |
2013 | πΉ | Model-based | Paper | ||
| Multi-scale boosted dehazing network with dense feature fusion Hang Dong, Jinshan Pan, Lei Xiang, Zhe Hu, Xinyi Zhang, Fei Wang, Ming-Hsuan Yang |
CVPR | 2020 | π· | Paper | ||
| Deep multi-model fusion for single-image dehazing Zijun Deng, Lei Zhu, Xiaowei Hu, Chi-Wing Fu, Xuemiao Xu, Qing Zhang, Jing Qin, Pheng-Ann Heng |
ICCV | 2019 | π· | Paper | ||
| Image dehazing by artificial multiple-exposure image fusion A. Galdran |
2018 | π· | Fusion-based | Paper | ||
| A survey of image dehazing approaches C. Chengtao, Z. Qiuyu, L. Yanhua |
2015 | π· | Survey | Paper | ||
| Depth information assisted collaborative mutual promotion network for single image dehazing Yafei Zhang, Shen Zhou, Huafeng Li |
CVPR | 2024 | π· | Paper | ||
| IDGCP: Image dehazing based on gamma correction prior Mingye Ju, Can Ding, Y. Jay Guo, Dengyin Zhang |
TIP | 2019 | π· | Paper | ||
| You only look yourself: Unsupervised and untrained single image dehazing neural network Boyun Li, Yuanbiao Gou, Shuhang Gu, Jerry Zitao Liu, Joey Tianyi Zhou, Xi Peng |
IJCV | 2021 | π· | Paper | ||
| Mixdehazenet: Mix structure block for image dehazing network Liping Lu, Qian Xiong, Bingrong Xu, Duanfeng Chu |
2024 | π· | CNN | Paper | Code | |
| IDRLP: Image dehazing using region line prior Mingye Ju, Can Ding, Charles A. Guo, Wenqi Ren, Dacheng Tao |
TIP | 2021 | π· | Paper | ||
| Night-time dehazing by fusion Cosmin Ancuti, Codruta O. Ancuti, Christophe De Vleeschouwer, Alan C. Bovik |
ICIP | 2016 | π· | Paper | ||
| Detection-friendly dehazing: Object detection in real-world hazy scenes Chengyang Li, Heng Zhou, Yang Liu, Caidong Yang, Yongqiang Xie, Zhongbo Li, Liping Zhu |
TPAMI | 2023 | π· | Paper | ||
| Self-guided image dehazing using progressive feature fusion Haoran Bai, Jinshan Pan, Xinguang Xiang, Jinhui Tang |
TIP | 2022 | π· | Paper | ||
| Ridcp: Revitalizing real image dehazing via high-quality codebook priors Rui-Qi Wu, Zheng-Peng Duan, Chun-Le Guo, Zhi Chai, Chongyi Li |
CVPR | 2023 | π· | Paper | ||
| On the duality between retinex and image dehazing Adrian Galdran, Aitor Alvarez-Gila, Alessandro Bria, Javier Vazquez-Corral, Marcelo BertalmΓo |
CVPR | 2018 | π· | Paper | ||
| From synthetic to real: Image dehazing collaborating with unlabeled real data Ye Liu, Lei Zhu, Shunda Pei, Huazhu Fu, Jing Qin, Qing Zhang, Liang Wan, Wei Feng |
2021 | π· | Paper | |||
| A comprehensive survey and taxonomy on single image dehazing based on deep learning Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, Jiuxin Cao, Dacheng Tao |
2023 | π· | Survey | Paper | ||
| Single image dehazing using color ellipsoid prior Trung Minh Bui, Wonha Kim |
TIP | 2017 | π· | Paper | ||
| A cascaded convolutional neural network for single image dehazing Chongyi Li, Jichang Guo, Fatih Porikli, Huazhu Fu, Yanwei Pang |
2018 | π· | CNN | Paper | Code | |
| Single image dehazing through improved atmospheric light estimation Huimin Lu, Yujie Li, Shota Nakashima, Seiichi Serikawa |
Multimed Tools Appl. | 2016 | π· | Paper | ||
| Improved wavelet transform algorithm for single image dehazing Zhu Rong, Wang Li Jun |
2014 | π· | Model-based | Paper | ||
| Uncertainty-driven dehazing network Ming Hong, Jianzhuang Liu, Cuihua Li, Yanyun Qu |
AAAI | 2022 | π· | Paper | ||
| Ultra-high-definition image dehazing via multi-guided bilateral learning Zhuoran Zheng, Wenqi Ren, Xiaochun Cao, Xiaobin Hu, Tao Wang, Fenglong Song, Xiuyi Jia |
CVPR | 2021 | π· | Paper | ||
| Multi-scale single image dehazing using perceptual pyramid deep network He Zhang, Vishwanath Sindagi, Vishal M. Patel |
CVPR | 2018 | π· | Paper | ||
| Single image dehazing via multi-scale convolutional neural networks with holistic edges Wenqi Ren, Jinshan Pan, Hua Zhang, Xiaochun Cao, Ming-Hsuan Yang |
IJCV | 2020 | π· | Paper | ||
| Single image dehazing using color attenuation prior. Qingsong Zhu, Jiaming Mai, Ling Shao |
2014 | π· | Model-based | Paper | Code | |
| Progressive feature fusion network for realistic image dehazing Kangfu Mei, Aiwen Jiang, Juncheng Li, Mingwen Wang |
ACCV | 2018 | π· | Paper | ||
| Advancing real-world image dehazing: Perspective, modules, and training Yuxin Feng, Long Ma, Xiaozhe Meng, Fan Zhou, Risheng Liu, Zhuo Su |
TPAMI | 2024 | π· | Paper | ||
| Fusion-based variational image dehazing Adrian Galdran, Javier Vazquez-Corral, David Pardo, Marcelo Bertalmio |
2016 | π· | Variational | Paper | ||
| Self-augmented unpaired image dehazing via density and depth decomposition Yang Yang, Chaoyue Wang, Risheng Liu, Lin Zhang, Xiaojie Guo, Dacheng Tao |
CVPR | 2022 | π· | Paper | ||
| Image dehazing via enhancement, restoration, and fusion: A survey Xiaojie Guo, Yang Yang, Chaoyue Wang, Jiayi Ma |
2022 | π· | Survey | Paper | ||
| Improved single image dehazing using geometry Peter Carr, Richard Hartley |
2009 | π· | Model-based | Paper | ||
| Fast image dehazing using guided joint bilateral filter Chunxia Xiao, Jiajia Gan |
Vis Comput | 2012 | π· | Paper | ||
| PDR-Net: Perception-inspired single image dehazing network with refinement Chongyi Li, Chunle Guo, Jichang Guo, Ping Han, Huazhu Fu, Runmin Cong |
2019 | π· | CNN | Paper | ||
| A novel fast single image dehazing algorithm based on artificial multiexposure image fusion Zhiqin Zhu, Hongyan Wei, Gang Hu, Yuanyuan Li, Guanqiu Qi, Neal Mazur |
TIM | 2020 | π· | Paper | ||
| Multi-scale optimal fusion model for single image dehazing Dong Zhao, Long Xu, Yihua Yan, Jie Chen, Ling-Yu Duan |
2019 | π· | Fusion-based | Paper | Code | |
| Single image dehazing with a generic model-agnostic convolutional neural network Zheng Liu, Botao Xiao, Muhammad Alrabeiah, Keyan Wang, Jun Chen |
2019 | π· | CNN | Paper | Code | |
| LIDN: a novel light invariant image dehazing network Asfak Ali, Avra Ghosh, Sheli Sinha Chaudhuri |
2023 | π· | CNN | Paper | ||
| Proximal dehaze-net: A prior learning-based deep network for single image dehazing Dong Yang, Jian Sun |
ECCV | 2018 | π· | Paper | ||
| Single image dehazing using a multilayer perceptron SebastiΓ‘n Salazar-Colores, Ivan Cruz-Aceves |
JEI | 2018 | π· | Paper | ||
| Gated context aggregation network for image dehazing and deraining Dongdong Chen, Mingming He, Qingnan Fan, Jing Liao, Liheng Zhang, Dongdong Hou, Lu Yuan, Gang Hua |
WACV | 2019 | π· | Paper | ||
| PSD: Principled synthetic-to-real dehazing guided by physical priors Zeyuan Chen, Yangchao Wang, Yang Yang, Dong Liu |
CVPR | 2021 | π· | Paper | ||
| Blind dehazing using internal patch recurrence Yuval Bahat, Michal Irani |
2016 | π· | Paper | Code | ||
| Video dehazing with spatial and temporal coherence Jiawan Zhang, Liang Li, Yi Zhang, Guoqiang Yang, Xiaochun Cao, Jizhou Sun |
Vis Comput | 2011 | πΉ | Paper | ||
| Single image dehazing using improved cycleGAN B.S.N.V. Chaitanya, Snehasis Mukherjee |
JVCIR | 2021 | π· | GAN | Paper | Code |
| Recent advances in image dehazing: Formal analysis to automated approaches Bhawna Goyal, Ayush Dogra, Dawa Chyophel Lepcha, Vishal Goyal, Ahmed Alkhayyat, Jasgurpreet Singh Chohan, Vinay Kukreja |
2024 | π· | Survey | Paper | ||
| ICycleGAN: Single image dehazing based on iterative dehazing model and CycleGAN Ziyi Sun, Yunfeng Zhang, Fangxun Bao, Kai Shao, Xinxin Liu, Caiming Zhang |
2021 | π· | GAN | Paper | ||
| Fast single image dehazing using saturation based transmission map estimation Se Eun Kim, Tae Hee Park, Il Kyu Eom |
TIP | 2019 | π· | Paper | ||
| Single image dehazing using a new color channel Geet Sahu, Ayan Seal, Ondrej Krejcar, Anis Yazidi |
JVCIR | 2021 | π· | Paper | Code | |
| Real-time dehazing for image and video Xingyong Lv, Wenbin Chen, I-fan Shen |
2010 | πΉ | Paper | Code | ||
| AIPNet: Image-to-image single image dehazing with atmospheric illumination prior Anna Wang, Wenhui Wang, Jinglu Liu, Nanhui Gu |
TIP | 2018 | π· | Paper | ||
| I-HAZE: A dehazing benchmark with real hazy and haze-free indoor images Cosmin Ancuti, Codruta O. Ancuti, Radu Timofte, Christophe De Vleeschouwer |
2018 | π· | Benchmark | Paper | ||
| AED-Net: A single image dehazing Sargis A. Hovhannisyan, Hayk A. Gasparyan, Sos S. Agaian, Art Ghazaryan |
2022 | π· | CNN | Paper | ||
| NH-HAZE: An image dehazing benchmark with non-homogeneous hazy and haze-free images Codruta O. Ancuti, Cosmin Ancuti, Radu Timofte |
CVPR | 2020 | π· | Paper | ||
| Fast image dehazing using improved dark channel prior Haoran Xu, Jianming Guo, Qing Liu, Lingli Ye |
2012 | π· | Model-based | Paper | Code | |
| Fsad-net: feedback spatial attention dehazing network Yu Zhou, Zhihua Chen, Ping Li, Haitao Song, C. L. Philip Chen, Bin Sheng |
2022 | π· | CNN | Paper | ||
| Towards domain invariant single image dehazing Pranjay Shyam, Kuk-Jin Yoon, Kyung-Soo Kim |
AAAI | 2021 | π· | Paper | ||
| DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention Zixuan Chen, Zewei He, Zhe-Ming Lu |
TIP | 2024 | π· | Paper | ||
| LKD-Net: Large kernel convolution network for single image dehazing Pinjun Luo, Guoqiang Xiao, Xinbo Gao, Song Wu |
2023 | π· | CNN | Paper | ||
| Mb-taylorformer: Multi-branch efficient transformer expanded by taylor formula for image dehazing Yuwei Qiu, Kaihao Zhang, Chenxi Wang, Wenhan Luo, Hongdong Li, Zhi Jin |
ICCV | 2023 | π· | Paper | ||
| IDE: Image dehazing and exposure using an enhanced atmospheric scattering model Mingye Ju, Can Ding, Wenqi Ren, Yi Yang, Dengyin Zhang, Y. Jay Guo |
TIP | 2021 | π· | Paper | ||
| A fast image dehazing algorithm based on negative correction Yuanyuan Gao, Hai-Miao Hu, Shuhang Wang, Bo Li |
2014 | π· | Paper | Code | ||
| Single image dehazing with an independent detail-recovery network Yan Li, De Cheng, Dingwen Zhang, Nannan Wang, Xinbo Gao, Jiande Sun |
2022 | π· | CNN | Paper | ||
| DRCDN: learning deep residual convolutional dehazing networks Shengdong Zhang, Fazhi He |
Vis Comput | 2020 | π· | Paper | ||
| Single image dehazing with a physical model and dark channel prior Jin-Bao Wang, Ning He, Lu-Lu Zhang, Ke Lu |
2015 | π· | Model-based | Paper | ||
| Distilling image dehazing with heterogeneous task imitation Ming Hong, Yuan Xie, Cuihua Li, Yanyun Qu |
CVPR | 2020 | π· | Paper | ||
| Single image dehazing using deep neural networks Nisarg Doshi, Sagar Bhavsar, Rajeswari D, Srinivasan R |
2019 | π· | CNN | Paper | ||
| Multi-level feature interaction and efficient non-local information enhanced channel attention for image dehazing Hang Sun, Bohui Li, Zhiping Dan, Wei Hu, Bo Du, Wen Yang, Jun Wan |
2023 | π· | Model-based | Paper | ||
| Unsupervised multi-branch network with high-frequency enhancement for image dehazing Hang Sun, Zhiming Luo, Dong Ren, Bo Du, Laibin Chang, Jun Wan |
PR | 2024 | π· | Paper | ||
| Dehazing for images with large sky region Wencheng Wang, Xiaohui Yuan, Xiaojin Wu, Yunlong Liu |
2017 | π· | Model-based | Paper | ||
| Single image dehazing using the change of detail prior Jiafeng Li, Hong Zhang, Ding Yuan, Mingui Sun |
2015 | π· | Model-based | Paper | ||
| Color channel transfer for image dehazing Codruta Orniana Ancuti, Cosmin Ancuti, Christophe De Vleeschouwer, Mateu Sbetr |
2019 | π· | Model-based | Paper | ||
| Progressive negative enhancing contrastive learning for image dehazing and beyond De Cheng, Yan Li, Dingwen Zhang, Nannan Wang, Jiande Sun, Xinbo Gao |
2024 | π· | Contrastive Learning | Paper | ||
| Delving deeper into image dehazing: A survey Guohou Li, Jia Li, Gongchao Chen, Zhibin Wang, Songlin Jin, Chang Ding, Weidong Zhang |
2023 | π· | Survey | Paper | ||
| Pyramid global context network for image dehazing Dong Zhao, Long Xu, Lin Ma, Jia Li, Yihua Yan |
TCSVT | 2020 | π· | Paper | ||
| QCNN-H: Single-image dehazing using quaternion neural networks Vladimir Frants, Sos Agaian, Karen Panetta |
2023 | π· | CNN | Paper | ||
| Day and night-time dehazing by local airlight estimation Cosmin Ancuti, Codruta O. Ancuti, Christophe De Vleeschouwer, Alan C. Bovik |
TIP | 2020 | π· | Paper | ||
| Dense-haze: A benchmark for image dehazing with dense-haze and haze-free images Codruta O. Ancuti, Cosmin Ancuti, Mateu Sbert, Radu Timofte |
ICIP | 2019 | π· | Paper | ||
| Dehazing for multispectral remote sensing images based on a convolutional neural network with the residual architecture Manjun Qin, Fengying Xie, Wei Li, Zhenwei Shi, Haopeng Zhang |
2018 | π· | CNN | Paper | ||
| Single image dehazing using CNN Huzaifa Rashid, Nauman Zafar, M Javed Iqbal, Hassan Dawood, Hussain Dawood |
2019 | π· | CNN | Paper | Code | |
| Generative adversarial and self-supervised dehazing network Shengdong Zhang, Xiaoqin Zhang, Shaohua Wan, Wenqi Ren, Liping Zhao, Linlin Shen |
2023 | π· | GAN | Paper | ||
| IDeRs: Iterative dehazing method for single remote sensing image Long Xu, Dong Zhao, Yihua Yan, Sam Kwong, Jie Chen, Ling-Yu Duan |
2019 | π· | Paper | Code | ||
| Dual-scale single image dehazing via neural augmentation Zhengguo Li, Chaobing Zheng, Haiyan Shu, Shiqian Wu |
TIP | 2022 | π· | Paper | ||
| Single image dehazing via NIN-DehazeNet Kangle Yuan, Jianguo Wei, Wenhuan Lu, Naixue Xiong |
2019 | π· | Paper | Code | ||
| A database with reference for image dehazing evaluation Jessica El Khoury, Jean-Baptiste Thomas, Alamin Mansouri |
2018 | π· | Benchmark | Paper | ||
| USID-Net: Unsupervised single image dehazing network via disentangled representations Jiafeng Li, Yaopeng Li, Li Zhuo, Lingyan Kuang, Tianjian Yu |
2022 | π· | Unsupervised | Paper | Code | |
| A novel bi-stream network for image dehazing Qiaoyu Ma, Shijie Wang, Guowei Yang, Chenglizhao Chen, Teng Yu |
2024 | π· | CNN | Paper | ||
| Underwater image dehazing using joint trilateral filter Seiichi Serikawa, Huimin Lu |
2014 | π· | Paper | |||
| Deep retinex network for single image dehazing Pengyue Li, Jiandong Tian, Yandong Tang, Guolin Wang, Chengdong Wu |
TIP | 2020 | π· | Paper | ||
| A comprehensive survey on image dehazing for different atmospheric scattering models Shunmin An, Xixia Huang, Lujia Cao, Linling Wang |
Multimed Tools Appl. | 2024 | π· | Paper | ||
| Nighttime dehazing with a synthetic benchmark Jing Zhang, Yang Cao, Zheng-Jun Zha, Dacheng Tao |
2020 | π· | Benchmark | Paper | ||
| Joint transmission map estimation and dehazing using deep networks He Zhang, Vishwanath Sindagi, Vishal M. Patel |
TCSVT | 2019 | π· | Paper | ||
| High-quality image dehazing with diffusion model Hu Yu, Jie Huang, Kaiwen Zheng, Feng Zhao |
ArXiv | 2308 | π· | Paper | ||
| Trinity-net: Gradient-guided swin transformer-based remote sensing image dehazing and beyond Kaichen Chi, Yuan Yuan, Qi Wang |
2023 | π· | Transformer | Paper | ||
| Improved single image dehazing using segmentation Shuai Fang, Jiqing Zhan, Yang Cao, Ruizhong Rao |
ICIP | 2010 | π· | Paper | ||
| Image dehazing using deep learning techniques Ravi Raj Choudhary, K K Jisnu, Gaurav Meena |
2020 | π· | CNN | Paper | ||
| Deep learning based single image dehazing Patricia L. Suarez, Angel D. Sappa, Boris X. Vintimilla, Riad I. Hammoud |
CVPR | 2018 | π· | Paper | ||
| Towards compact single image dehazing via task-related contrastive network Weichao Yi, Liquan Dong, Ming Liu, Mei Hui, Lingqin Kong, Yuejin Zhao |
2024 | π· | Contrastive Learning | Paper | ||
| A region-wised medium transmission based image dehazing method Hui Yuan, Changchun Liu, Zhixin Guo, Zhenzhen Sun |
2017 | π· | Model-based | Paper | ||
| Deep hybrid model for single image dehazing and detail refinement Nanfeng Jiang, Kejian Hu, Ting Zhang, Weiling Chen, Yiwen Xu, Tiesong Zhao |
PR | 2023 | π· | Paper | ||
| Multi-scale single image dehazing using Laplacian and Gaussian pyramids Zhengguo Li, Haiyan Shu, Chaobing Zheng |
TIP | 2021 | π· | Paper | ||
| PhDnet: A novel physic-aware dehazing network for remote sensing images Ziyang Lihe, Jiang He, Qiangqiang Yuan, Xianyu Jin, Yi Xiao, Liangpei Zhang |
2024 | π· | CNN | Paper | ||
| Frequency compensated diffusion model for real-scene dehazing Jing Wang, Songtao Wu, Zhiqiang Yuan, Qiang Tong, Kuanhong Xu |
2024 | π· | Diffusion | Paper | ||
| Image dehazing by an artificial image fusion method based on adaptive structure decomposition Mingyao Zheng, Guanqiu Qi, Zhiqin Zhu, Yuanyuan Li, Hongyan Wei, Yu Liu |
2020 | π· | Fusion-based | Paper | ||
| DENSE123'COLOR Enhancement Dehazing Network Tiantong Guo, Venkateswararao Cherukuri, Vishal Monga |
CVPR | 2019 | π· | Paper | ||
| Unsupervised single image dehazing using dark channel prior loss Alona Golts, Daniel Freedman, Michael Elad |
TIP | 2019 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Citations | Data | Link | Code |
|---|---|---|---|---|---|---|
| Progressive image deraining networks: A better and simpler baseline | CVPR | 2019 | 935 | π· | Paper | Code |
| Single image deraining: From model-based to data-driven and beyond | TPAMI | 2021 | 262 | π· | Paper | |
| Data-driven single image deraining: A comprehensive review and new perspectives | PR | 2021 | 69 | π· | Paper | |
| Single image deraining: A comprehensive benchmark analysis | CVPR | 2019 | 329 | π· | Paper | |
| Multi-scale progressive fusion network for single image deraining | CVPR | 2023 | 740 | π· | Paper | Code |
| Learning a sparse transformer network for effective image deraining | CVPR | 2023 | 388 | π· | Paper | Code |
| Towards unified deep image deraining: A survey and a new benchmark | TPAMI | 2025 | 44 | π· | Paper | |
| Residual-guide network for single image deraining | ACMMM | 2023 | 142 | π· | Paper | |
| Detail-recovery image deraining via context aggregation networks | CVPR | 2020 | 140 | π· | Paper | |
| Spatial attentive single-image deraining with a high quality real rain dataset | CVPR | 2019 | 518 | π· | Paper | |
| Conditional variational image deraining | TIP | 2020 | 85 | π· | Paper | Code |
| Lightweight pyramid networks for image deraining | TNNLS | 2020 | 375 | π· | Paper | |
| Single image deraining using bilateral recurrent network | TIP | 2020 | 92 | π· | Paper | Code |
| Freqmamba: Viewing mamba from a frequency perspective for image deraining | ACMMM | 2024 | 78 | π· | Paper | |
| Syn2real transfer learning for image deraining using gaussian processes | CVPR | 2020 | 195 | π· | Paper | |
| A comprehensive benchmark analysis of single image deraining: Current challenges and future perspectives | IJCV | 2021 | 66 | π· | Paper | |
| Multi-scale fusion and decomposition network for single image deraining | TIP | 2024 | 39 | π· | Paper | Code |
| Robust representation learning with feedback for single image deraining | CVPR | 2021 | 92 | π· | Paper | Code |
| Video desnowing and deraining based on matrix decomposition | CVPR | 2017 | 156 | π· | Paper | |
| Smartassign: Learning a smart knowledge assignment strategy for deraining and desnowing | CVPR | 2023 | 30 | π· | Paper | |
| Unpaired deep image deraining using dual contrastive learning | CVPR | 2022 | 175 | π· | Paper | |
| Beyond monocular deraining: Stereo image deraining via semantic understanding | ECCV | 2020 | 52 | π· | Paper | |
| Rethinking multi-scale representations in deep deraining transformer | AAAI | 2024 | 27 | π· | Paper | |
| Recurrent squeeze-and-excitation context aggregation net for single image deraining | ECCV | 2018 | 614 | π· | Paper | |
| Multi-scale hybrid fusion network for single image deraining | TNNLS | 2023 | 49 | π· | Paper | Code |
| Efficientderain: Learning pixel-wise dilation filtering for high-efficiency single-image deraining | AAAI | 2021 | 108 | π· | Paper | Code |
| Beyond monocular deraining: Parallel stereo deraining network via semantic prior | IJCV | 2022 | 63 | π· | Paper | Code |
| Unsupervised deraining: Where contrastive learning meets self-similarity | CVPR | 2022 | 67 | π· | Paper | |
| Deraincyclegan: Rain attentive cyclegan for single image deraining and rainmaking | TIP | 2021 | 193 | π· | Paper | |
| Memory oriented transfer learning for semi-supervised image deraining | CVPR | 2021 | 108 | π· | Paper | |
| Rethinking image deraining via rain streaks and vapors | ECCV | 2020 | 59 | π· | Paper | Code |
| Dreaming to prune image deraining networks | CVPR | 2022 | 21 | π· | Paper | |
| FMRNet: Image deraining via frequency mutual revision | AAAI | 2024 | 10 | π· | Paper | Code |
| Hybrid cnn-transformer feature fusion for single image deraining | AAAI | 2023 | 68 | π· | Paper | Code |
| Residual multiscale based single image deraining | BMVC | 2023 | 48 | π· | Paper | |
| Sginet: Toward sufficient interaction between single image deraining and semantic segmentation | ACMMM | 2022 | 32 | π· | Paper | |
| Drt: A lightweight single image deraining recursive transformer | CVPRW | 2022 | 62 | π· | Paper | Code |
| Not just streaks: Towards ground truth for single image deraining | ECCV | 2022 | 52 | π· | Paper | |
| Networks are slacking off: Understanding generalization problem in image deraining | NeurIPS | 2025 | 17 | π· | Paper | |
| Semi-supervised image deraining using knowledge distillation | TCSVT | 2022 | 60 | π· | Paper | Code |
| Continual image deraining with hypergraph convolutional networks | TPAMI | 2023 | 50 | π· | Paper | |
| Bidirectional multi-scale implicit neural representations for image deraining | CVPR | 2024 | 81 | π· | Paper | Code |
| Memory uncertainty learning for real-world single image deraining | TPAMI | 2023 | 23 | π· | Paper | |
| A two-stage density-aware single image deraining method | TIP | 2021 | 17 | π· | Paper | |
| Single image deraining via recurrent hierarchy enhancement network | ACMMM | 2019 | 61 | π· | Paper | |
| A coarse-to-fine multi-stream hybrid deraining network for single image deraining | ICDM | 2019 | 35 | π· | Paper | |
| Frame-consistent recurrent video deraining with dual-level flow | CVPR | 2019 | 111 | π· | Paper | |
| Rain-free and residue hand-in-hand: A progressive coupled network for real-time image deraining | TIP | 2021 | 153 | π· | Paper | Code |
| Danet: Image deraining via dynamic association learning. | IJCAI | 2022 | 24 | π· | Paper | |
| Efficient frequency-domain image deraining with contrastive regularization | ECCV | 2025 | 18 | π· | Paper | Code |
| Learning a spiking neural network for efficient image deraining | Image Processing | 2024 | 16 | π· | Paper | Code |
| Towards ultra-high-definition image deraining: A benchmark and an efficient method | ArXiv | 2024 | 0 | π· | Paper | Code |
| Toward real-world single image deraining: A new benchmark and beyond | ArXiv | 2022 | 0 | π· | Paper | Code |
| PFDN: Pyramid feature decoupling network for single image deraining | TIP | 2022 | 19 | π· | Paper | |
| Decomposition makes better rain removal: An improved attention-guided deraining network | TCSVT | 2021 | 94 | π· | Paper | Code |
| A hybrid transformer-mamba network for single image deraining | SIVP | 2024 | 14 | π· | Paper | |
| Semi-supervised image deraining using gaussian processes | TIP | 2021 | 19 | π· | Paper | Code |
| Multi-decoding deraining network and quasi-sparsity based training | CVPR | 2021 | 35 | π· | Paper | |
| Learning rain location prior for nighttime deraining | ICCV | 2023 | 26 | π· | Paper | Code |
| Single-image deraining via recurrent residual multiscale networks | TNNLS | 2022 | 31 | π· | Paper | |
| Rainmamba: Enhanced locality learning with state space models for video deraining | ACMMM | 2024 | 58 | π· | Paper | |
| Unpaired learning for deep image deraining with rain direction regularizer | ICCV | 2021 | 49 | π· | Paper | |
| Fouriermamba: Fourier learning integration with state space models for image deraining | ICASSP | 2024 | 24 | π· | Paper | |
| Structure-preserving deraining with residue channel prior guidance | ICCV | 2021 | 140 | π· | Paper | Code |
| Magic ELF: Image deraining meets association learning and transformer | ACMMM | 2022 | 79 | π· | Paper | Code |
| Scale-free single image deraining via visibility-enhanced recurrent wavelet learning | TIP | 2019 | 101 | π· | Paper | |
| Intensity-aware single-image deraining with semantic and color regularization | TIP | 2021 | 24 | π· | Paper | |
| Dilated convolutional transformer for high-quality image deraining | CVPRW | 2023 | 22 | π· | Paper | |
| Wavelet approximation-aware residual network for single image deraining | TPAMI | 2023 | 22 | π· | Paper | |
| Semi-supervised video deraining with dynamical rain generator | CVPR | 2021 | 79 | π· | Paper | |
| Deep scale-space mining network for single image deraining | CVPRW | 2022 | 18 | π· | Paper | |
| Unsupervised image deraining: Optimization model driven deep cnn | ACMMM | 2021 | 36 | π· | Paper | |
| Residual-guide feature fusion network for single image deraining | ACMMM | 2018 | 142 | π· | Paper | |
| Semi-swinderain: Semi-supervised image deraining network using swin transformer | ICASSP | 2023 | 9 | π· | Paper | Code |
| Unsupervised video deraining with an event camera | ICCV | 2023 | 18 | π· | Paper | |
| Enhanced spatio-temporal interaction learning for video deraining: faster and better | TPAMI | 2023 | 112 | π· | Paper | Code |
| Recurrent multi-frame deraining: Combining physics guidance and adversarial learning | TPAMI | 2021 | 21 | π· | Paper | Code |
| Context-enhanced representation learning for single image deraining | IJCV | 2021 | 24 | π· | Paper | Code |
| Single image deraining using time-lapse data | TIP | 2020 | 8 | π· | Paper | |
| Utilizing two-phase processing with FBLS for single image deraining | TMM | 2021 | 28 | π· | Paper | |
| Dawn: Direction-aware attention wavelet network for image deraining | ACMMM | 2023 | 43 | π· | Paper | |
| Selective wavelet attention learning for single image deraining | IJCV | 2021 | 52 | π· | Paper | |
| Dual heterogeneous complementary networks for single image deraining | CVPRW | 2022 | 13 | π· | Paper | |
| Single image deraining with continuous rain density estimation | TMM | 2023 | 30 | π· | Paper | |
| Video deraining and desnowing using temporal correlation and low-rank matrix completion | TIP | 2015 | 222 | π· | Paper | |
| Image deraining with frequency-enhanced state space model | ECCV | 2025 | 9 | π· | Paper | Code |
| DRD-Net: Detail-recovery image deraining via context aggregation networks | CVPR | 2019 | 48 | π· | Paper | |
| Online-updated high-order collaborative networks for single image deraining | AAAI | 2022 | 26 | π· | Paper | |
| An end-to-end cascaded image deraining and object detection neural network | RA-L | 2022 | 21 | π· | Paper | |
| RCDNet: An interpretable rain convolutional dictionary network for single image deraining | TNNLS | 2024 | 48 | π· | Paper | Code |
| A two-stage network with wavelet transformation for single-image deraining | TVC | 2023 | 14 | π· | Paper | Code |
| Explore internal and external similarity for single image deraining with graph neural networks | IJCAI | 2024 | 7 | π· | Paper | Code |
| Joint self-attention and scale-aggregation for self-calibrated deraining network | ACMMM | 2020 | 76 | π· | Paper | |
| Deep single image deraining via modeling haze-like effect | TMM | 2021 | 23 | π· | Paper | |
| Nightrain: Nighttime video deraining via adaptive-rain-removal and adaptive-correction | AAAI | 2024 | 22 | π· | Paper | |
| Event-aware video deraining via multi-patch progressive learning | TIP | 2023 | 26 | π· | Paper | |
| Unrolling a rain-guided detail recovery network for singleimage deraining | Virtual Reality & Intelligent Hardware | 2023 | 18 | π· | Paper | |
| Recurrent wavelet structure-preserving residual network for single image deraining | PR | 2023 | 37 | π· | Paper | |
| Unsupervised deraining: Where asymmetric contrastive learning meets self-similarity | TPAMI | 2024 | 22 | π· | Paper | |
| Event-driven heterogeneous network for video deraining | IJCV | 2024 | 6 | π· | Paper | |
| Meta-learning based relation and representation learning networks for single-image deraining | PR | 2021 | 19 | π· | Paper | |
| Contrastive unfolding deraining network | TNNLS | 2024 | 8 | π· | Paper | |
| Rain2Avoid: Learning Deraining by Self-Supervision | TMM | 2025 | 1 | π· | Paper | |
| Self-aligned video deraining with transmission-depth consistency | CVPR | 2021 | 39 | π· | Paper | |
| Close the loop: A unified bottom-up and top-down paradigm for joint image deraining and segmentation | AAAI | 2022 | 28 | π· | Paper | |
| Image de-raining using a conditional generative adversarial network | TCSVT | 2020 | 1127 | π· | Paper | |
| Single-image deraining via a recurrent memory unit network | KBS | 2021 | 18 | π· | Paper | |
| Image de-raining transformer | TPAMI | 2023 | 286 | π· | Paper | |
| Local and global knowledge distillation with direction-enhanced contrastive learning for single-image deraining | KBS | 2023 | 23 | π· | Paper | |
| EfficientDeRain+: Learning Uncertainty-Aware Filtering via RainMix Augmentation for High-Efficiency Deraining | IJCV | 2025 | 3 | π· | Paper | Code |
| Distributed feedback network for single-image deraining | IS | 2021 | 11 | π· | Paper | |
| High-level task-driven single image deraining: Segmentation in rainy days | ECCV | 2020 | 14 | π· | Paper | |
| Pearl: Preprocessing enhanced adversarial robust learning of image deraining for semantic segmentation | ACMMM | 2023 | 10 | π· | Paper | |
| Triple-level model inferred collaborative network architecture for video deraining | TIP | 2022 | 25 | π· | Paper | Code |
| Neural SchrΓΆdinger bridge for unpaired real-world image deraining | IS | 2024 | 7 | π· | Paper | |
| Aggregating global and local representations via hybrid transformer for video deraining | TCSVT | 2024 | 10 | π· | Paper | |
| Single image deraining via deep shared pyramid network | TVC | 2021 | 15 | π· | Paper | |
| A convolutional network for joint deraining and dehazing from a single image for autonomous driving in rain | IROS | 2019 | 23 | π· | Paper | |
| Deep image deraining | ICM | 2023 | 175 | π· | Paper | |
| GKC-Net: gated KAN with Channel-Position attention mechanism for image deraining | PR | 2026 | 1 | π· | Paper | |
| Rethinking video rain streak removal: A new synthesis model and a deraining network with video rain prior | ECCV | 2022 | 21 | π· | Paper | Code |
| Single image deraining via decorrelating the rain streaks and background scene in gradient domain | PR | 2018 | 40 | π· | Paper | |
| Multi-scale hourglass hierarchical fusion network for single image deraining | CVPRW | 2021 | 23 | π· | Paper | Code |
| Unpaired photo-realistic image deraining with energy-informed diffusion model | ACMMM | 2024 | 10 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Data | Link | Code |
|---|
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| Attentive generative adversarial network for raindrop removal from a single image Rui Qian, Robby T. Tan, Wenhan Yang, Jiajun Su, Jiaying Liu |
CVPR | 2018 | π· | Paper | ||
| Learning from synthetic photorealistic raindrop for single image raindrop removal Zhixiang Hao, Shaodi You, Yu Li, Kunming Li, Feng Lu |
ICCV | 2019 | π· | Paper | ||
| Adherent raindrop modeling, detection and removal in video Shaodi You, Robby T. Tan, Rei Kawakami, Yasuhiro Mukaigawa, Katsushi Ikeuchi |
TPAMI | 2015 | πΉ | Paper | ||
| Raindrop clarity: A dual-focused dataset for day and night raindrop removal Yeying Jin, Xin Li, Jiadong Wang, Yan Zhang, Malu Zhang |
ECCV | 2024 | π· | Paper | ||
| Raingan: Unsupervised raindrop removal via decomposition and composition Xu Yan, Yuan Ren Loke |
WACV | 2022 | π· | Paper | ||
| Dual attention-in-attention model for joint rain streak and raindrop removal Kaihao Zhang, Dongxu Li, Wenhan Luo, Wenqi Ren |
TIP | 2021 | π· | Paper | ||
| Adherent raindrop detection and removal in video Shaodi You, Robby T. Tan, Rei Kawakami, Katsushi Ikeuchi |
CVPR | 2013 | πΉ | Paper | ||
| Feature-aligned video raindrop removal with temporal constraints Wending Yan, Lu Xu, Wenhan Yang, Robby T. Tan |
TIP | 2022 | πΉ | Paper | ||
| Dual-pixel raindrop removal Yizhou Li, Yusuke Monno, Masatoshi Okutomi |
TPAMI | 2024 | π· | Paper | ||
| Uncertainty guided multi-scale attention network for raindrop removal from a single image Ming-Wen Shao, Le Li, De-Yu Meng, Wang-Meng Zuo |
TIP | 2021 | π· | Paper | ||
| Removing raindrops and rain streaks in one go Ruijie Quan, Xin Yu, Yuanzhi Liang, Yi Yang |
CVPR | 2021 | π· | Paper | ||
| STRRNet: Semantics-guided two-stage raindrop removal network Qiyu Rong, Hongyuan Jing, Mengmeng Zhang, Jinlong Li, Mengfei Han |
CVPR | 2025 | π· | Paper | ||
| Uav-rain1k: A benchmark for raindrop removal from uav aerial imagery Wenhui Chang, Hongming Chen, Xin He, Xiang Chen, Liangduo Shen |
CVPR | 2024 | π· | Paper | ||
| Raindrop detection and removal from long range trajectories Shaodi You, Robby T. Tan, Rei Kawakami, Yasuhiro Mukaigawa, Katsushi Ikeuchi |
ACCV | 2014 | π· | Paper | ||
| Raindrop detection and removal using salient visual features Qi Wu, Wende Zhang, B.V.K. Vijaya Kumar |
ICIP | 2012 | π· | Paper | ||
| UnfairGAN: An enhanced generative adversarial network for raindrop removal from a single image Duc Manh Nguyen, Thao Phuong Le, Duc My Vo, Sang-Woong Lee |
2022 | π· | GAN | Paper | ||
| Context and detail interaction network for stereo rain streak and raindrop removal Jing Nie, Jin Xie, Jiale Cao, Yanwei Pang |
2023 | π· | CNN | Paper | ||
| Joint raindrop and haze removal from a single image Yina Guo, Jianguo Chen, Xiaowen Ren, Anhong Wang, Wenwu Wang |
TIP | 2020 | π· | Paper | ||
| NTIRE 2025 challenge on day and night raindrop removal for dual-focused images: Methods and results Xin Li, Yeying Jin, Xin Jin, Zongwei Wu, Bingchen Li, Yufei Wang, Wenhan Yang, Yu Li, Zhibo Chen, Bihan Wen, Robby Tan, Radu Timofte, Qiyu Rong, Hongyuan Jing, Mengmeng Zhang, Jinglong Li, Xiangyu Lu, Yi Ren, Yuting Liu, Meng Zhang, Xiang Chen, Qiyuan Guan, Jiangxin Dong, Jinshan Pan, Conglin Gou, Qirui Yang, Fangpu Zhang, Yunlong Lin, Sixiang Chen, Guoxi Huang, Ruirui Lin, Yan Zhang, Jingyu Yang, Huanjing Yue, Jiyuan Chen, Qiaosi Yi, Hongjun Wang, Chenxi Xie, Shuai Li, Yuhui Wu, Kaiyi Ma, Jiakui Hu, Juncheng Li, Liwen Pan, Guangwei Gao, Wenjie Li, Zhenyu Jin, Heng Guo, Zhanyu Ma, Yubo Wang, Jinghua Wang, Wangzhi Xing, Anjusree Karnavar, Diqi Chen, Mohammad Aminul Islam, Hao Yang, Ruikun Zhang, Liyuan Pan, Qianhao Luo, Xin Cao, Han Zhou, Yan Min, Wei Dong, Jun Chen, Taoyi Wu, Weijia Dou, Yu Wang, Shengjie Zhao, Yongcheng Huang, Xingyu Han, Anyan Huang, Hongtao Wu, Hong Wang, Yefeng Zheng, Abhijeet Kumar, Aman Kumar, Marcos V. Conde, Paula Garrido, Daniel Feijoo, Juan C. Benito, Guanglu Dong, Xin Lin, Siyuan Liu, Tianheng Zheng, Jiayu Zhong, Shouyi Wang, Xiangtai Li, Lanqing Guo, Lu Qi, Chao Ren, Shuaibo Wang, Shilong Zhang, Wanyu Zhou, Yunze Wu, Qinzhong Tan, Jieyuan Pei, Zhuoxuan Li, Jiayu Wang, Haoyu Bian, Haoran Sun, Subhajit Paul, Ni Tang, Junhao Huang, Zihan Cheng, Hongyun Zhu, Yuehan Wu, Kaixin Deng, Huang Ouyang, Tianxin Xiao, Fan Yang, Zhizun Luo, Zeyu Xiao, Zhuoyuan Li, Pham Hoang Le Nguyen, Dinh Thien An, Luu Thanh Son, Kiet Van Nguyen, Ronghua Xu, Xianmin Tian, Weijian Zhou, Jiacheng Zhang, Yuqian Chen, Yihang Duan, Yujie Wu, Suresh Raikwar, Arsh Garg, Kritika Kritika, Jianhua Zheng, Xiaoshan Ma, Ruolin Zhao, Yongyu Yang, Yongsheng Liang, Guiming Huang, Qiang Li, Hongbin Zhang, Xiangyu Zheng, A.N. Rajagopalan |
CVPR | 2025 | π· | Paper | ||
| Selective generative adversarial network for raindrop removal from a single image Mingwen Shao, Le Li, Hong Wang, Deyu Meng |
2021 | π· | GAN | Paper | ||
| Weakly supervised learning for raindrop removal on a single image Wenjie Luo, Jianhuang Lai, Xiaohua Xie |
TCSVT | 2020 | π· | Paper | ||
| A review of detection and removal of raindrops in automotive vision systems Yazan Hamzeh, Samir A. Rawashdeh |
2021 | π· | Survey | Paper | ||
| Adherent raindrop removal with self-supervised attention maps and spatio-temporal generative adversarial networks Stefano Alletto, Casey Carlin, Luca Rigazio, Yasunori Ishii, Sotaro Tsukizawa |
ICCV | 2019 | π· | Paper | ||
| Mask-guided progressive network for joint raindrop and rain streak removal in videos Hongtao Wu, Yijun Yang, Haoyu Chen, Jingjing Ren, Lei Zhu |
2023 | πΉ | CNN | Paper | ||
| Raindrop-removal image translation using target-mask network with attention module Hyuk-Ju Kwon, Sung-Hak Lee |
2023 | π· | CNN | Paper | ||
| Raindrop removal with light field image using image inpainting Tao Yang, Xiaofei Chang, Hang Su, Nathan Crombez, Yassine Ruichek, Tomas Krajnik, Zhi Yan |
2020 | π· | Benchmark | Paper | ||
| Laplacian encoder-decoder network for raindrop removal Simone Zini, Marco Buzzelli |
2022 | π· | CNN | Paper | ||
| Review on raindrop detection and removal in weather degraded images Mohd Helmy Abd Wahab, Ching-Hung Su, Nasriah Zakaria, Rosalina Abdul Salam |
2013 | π· | Survey | Paper | ||
| Raindrop removal from a single image using a two-step generative adversarial network Haiying Xia, Yang Lan, Shuxiang Song, Haisheng Li |
2022 | π· | Paper | |||
| Removal of rain in video based on motion and shape characteristics of raindrops Guili Xu, Jing Xu, Biao Wang, Yupeng Tian, Yongqiang Ye, Syed Ghafoor Shah |
2014 | πΉ | Paper | |||
| Adherent mist and raindrop removal from a single image using attentive convolutional network Da He, Xiaoyu Shang, Jiajia Luo |
2022 | π· | Paper | |||
| Unsupervised Network for Single Image Raindrop Removal Huijiao Wang, Shenghao Zhao, Lei Yu, Xulei Yang |
ArXiv | 2412 | π· | Paper | ||
| Robust attention deraining network for synchronous rain streaks and raindrops removal Yanyan Wei, Zhao Zhang, Mingliang Xu, Richang Hong, Jicong Fan, Shuicheng Yan |
2022 | π· | Paper | |||
| Removing raindrops from a single image using synthetic data Yoshihito Kokubo, Shusaku Asada, Hirotaka Maruyama, Masaru Koide, Kohei Yamamoto, Yoshihisa Suetsugu |
2020 | π· | Paper | |||
| A2Net: Adjacent Aggregation Networks for Image Raindrop Removal |
2020 | π· | Paper | |||
| Detection and removal of rain from videos K. Garg, S.K. Nayar |
CVPR | 2004 | πΉ | Paper | ||
| A survey of single image rain removal based on deep learning Zhipeng Su, Yixiong Zhang, Jianghong Shi, Xiao-Ping Zhang |
2023 | π· | Paper | |||
| Single-image raindrop removal using concurrent channel-spatial attention and long-short skip connections Jiayi Peng, Yong Xu, Tianyi Chen, Yan Huang |
2020 | π· | Paper | |||
| Rain drop detection and removal using k-means clustering M. Ramesh Kanthan, S. Naganandini Sujatha |
2015 | π· | Paper | |||
| Improved sea-ice identification using semantic segmentation with raindrop removal Nahed M. Alsharay, Yuanzhu Chen, Octavia A. Dobre, Oscar De Silva |
2022 | π· | Paper | |||
| All in one bad weather removal using architectural search Ruoteng Li, Robby T. Tan, Loong-Fah Cheong |
CVPR | 2020 | π· | Paper | ||
| Detection and removal of raindrop from images using deeplearning Y. Himabindu, R. Manjusha, Latha Parameswaran |
2019 | π· | Paper | |||
| Raindrop Removal for In-Vehicle Camera Images with Generative Adversarial Network Zihao Zhao, Min Jiang, Jia Guo, Xiaoyu Yang, Yudie Hu, Xianlong Zhou |
2022 | π· | Paper | |||
| Iterative contrastive learning for single image raindrop removal Yang Xulei, Qian Peisheng, Wang Li, Zhao Shenghao, Chen Cen, Li Xiaoli, Zeng Zeng |
ICIP | 2022 | π· | Paper | ||
| Removal of rain from videos: a review Abhishek Kumar Tripathi, Sudipta Mukhopadhyay |
2014 | πΉ | Paper | |||
| Image raindrop removal method for generative adversarial network based on difference learning Renhe Chen, Zhenyi Lai, Yurong Qian |
2020 | π· | Paper | |||
| Single Image Raindrop Removal Using a Non-Local Operator and Feature Maps in the Frequency Domain Shinya Ezumi, Masaaki Ikehara |
2022 | π· | Paper | |||
| Deep learning for seeing through window with raindrops Yuhui Quan, Shijie Deng, Yixin Chen, Hui Ji |
ICCV | 2019 | π· | Paper | ||
| Raindrop Removal using Image Inpainting M Nithyashree, Surabhi Narayan |
2023 | π· | Paper | |||
| Mutual channel prior guided dual-domain interaction network for single image raindrop removal Yuanjian Qiao, Mingwen Shao, Huan Liu, Kai Shang |
2023 | π· | Paper | |||
| Recovering raindrop removal images under heavy rain. Kosuke Matsumoto, Fumihiko Sakaue, Jun Sato |
ICCV | 2020 | π· | Paper | ||
| X-net for single image raindrop removal Jiamin Lin, Longquan Dai |
ICIP | 2020 | π· | Paper | ||
| Removing rain and snow in a single image using guided filter Jing Xu, Wei Zhao, Peng Liu, Xianglong Tang |
2012 | π· | Paper | |||
| Not All Areas Are Equal: A Novel SeparationβRestorationβFusion Network for Image Raindrop Removal Dongdong Ren, Jinbao Li, Meng Han, Minglei Shu |
2020 | π· | Paper | |||
| RIADNet: single image deraining network for raindrops and rain streaks removal Changle Yu, Ping Fan, Yi Zhang, Jiyu Yang |
2025 | π· | Paper | |||
| An Image Raindrop Removal Method Based on Squeeze-Excitation and Residual Fusion Yongsheng Shi, Lanxiang Gu |
2024 | π· | Paper | |||
| A dual CNN architecture for single image raindrop and rain streak removal Anparasy Sivaanpu, Kokul Thanikasalam |
2022 | π· | Paper | |||
| Raindropβimpactβinduced erosion processes and prediction: a review P. I. A. Kinnell |
2005 | π· | Paper | |||
| Cycle-spinning gan for raindrop removal from images Ulku Uzun, Alptekin Temizel |
2019 | π· | Paper | |||
| Application research on improved CGAN in image raindrop removal Min Zhu, Chao Fang, Haibo Du, Meibin Qi, Zhiwei Wu |
2019 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| All snow removed: Single image desnowing algorithm using hierarchical dual-tree complex wavelet representation and contradict channel loss |
2021 | π· | Paper | |||
| Smartassign: Learning a smart knowledge assignment strategy for deraining and desnowing Yinglong Wang, Chao Ma, Jianzhuang Liu |
CVPR | 2023 | π· | Paper | ||
| Video desnowing and deraining based on matrix decomposition Weihong Ren, Jiandong Tian, Zhi Han, Antoni Chan, Yandong Tang |
CVPR | 2017 | πΉ | Paper | ||
| A scalable and accurate de-snowing algorithm for LiDAR point clouds in winter Weiqi Wang, Xiong You, Lingyu Chen, Jiangpeng Tian, Fen Tang, Lantian Zhang |
2022 | π· | Paper | |||
| Hcsd-net: Single image desnowing with color space transformation Ting Zhang, Nanfeng Jiang, Hongxin Wu, Keke Zhang, Yuzhen Niu, Tiesong Zhao |
2023 | π· | Paper | |||
| Image desnowing via deep invertible separation Yuhui Quan, Xiaoheng Tan, Yan Huang, Yong Xu, Hui Ji |
TCSVT | 2023 | π· | Paper | ||
| Towards efficient single image dehazing and desnowing Tian Ye, Sixiang Chen, Yun Liu, Erkang Chen, Yuche Li |
ArXiv | 2204 | π· | Paper | ||
| Deep unfolding network for image desnowing with snow shape prior Xin Guo, Xi Wang, Xueyang Fu, Zheng-Jun Zha |
TCSVT | 2025 | π· | Paper | ||
| Enabling renewable energy technologies in harsh climates with ultraβefficient electroβthermal desnowing, defrosting, and deicing Longnan Li, Siavash Khodakarami, Xiao Yan, Kazi Fazle Rabbi, Ahmet Alperen Gunay, Andrew Stillwell, Nenad Miljkovic |
2022 | π· | Paper | |||
| Semi-supervised video desnowing network via temporal decoupling experts and distribution-driven contrastive regularization Hongtao Wu, Yijun Yang, Angelica I. Aviles-Rivero, Jingjing Ren, Sixiang Chen, Haoyu Chen, Lei Zhu |
ECCV | 2024 | πΉ | Paper | ||
| SnowFormer: Context interaction transformer with scale-awareness for single image desnowing Sixiang Chen, Tian Ye, Yun Liu, Erkang Chen |
ArXiv | 2208 | π· | Paper | ||
| Video deraining and desnowing using temporal correlation and low-rank matrix completion Jin-Hwan Kim, Jae-Young Sim, Chang-Su Kim |
TIP | 2015 | πΉ | Paper | ||
| Enhancing outdoor vision: Binocular desnowing with dual-stream temporal transformer En Yu, Jie Lu, Kaihao Zhang, Guangquan Zhang |
PR | 2026 | π· | Paper | ||
| De-snowing LiDAR point clouds with intensity and spatial-temporal features Boyang Li, Jieling Li, Gang Chen, Hejun Wu, Kai Huang |
ICRA | 2022 | π· | Paper | ||
| De-snowing algorithm for long-wavelength LiDAR Bharat Jayaprakash, Matthew Eagon, Lu Zhan, William F. Northrop |
2024 | π· | Paper | |||
| Fast and accurate desnowing algorithm for LiDAR point clouds Ji-Il Park, Jihyuk Park, Kyung-Soo Kim |
2020 | π· | Paper | |||
| LiDAR De-Snow Score (DSS): combining quality and perception metrics for optimised de-noising |
2025 | π· | Paper | |||
| Towards real-time high-definition image snow removal: Efficient pyramid network with asymmetrical encoder-decoder architecture Tian Ye, Sixiang Chen, Yun Liu, Yi Ye, Jinbin Bai, Erkang Chen |
ACCV | 2022 | π· | Paper | ||
| Dual gradient based snow attentive desnowing Guisik Kim, Sungmin Cho, Dokyeong Kwon, Seo Hyeon Lee, Junseok Kwon |
2023 | π· | Paper | |||
| An efficient video desnowing and deraining method with a novel variant dataset Arezoo Sadeghzadeh, Md Baharul Islam, Reza Zaker |
2021 | πΉ | Paper | |||
| Simultaneous snow mask prediction and single image desnowing with a bidirectional attention transformer network Yongheng Zhang, Danfeng Yan |
2024 | π· | Paper | |||
| LiDAR de-snowing method with density and intensity fusion Feng Pan, Wei Wang |
2023 | π· | Paper | |||
| An integrated multi-scale context-aware network for efficient desnowing Samuel Akwasi Agyemang, Haobin Shi, Xuan Nie, Nana Yaw Asabere |
2025 | π· | Paper | |||
| Event-Based De-Snowing for Autonomous Driving Manasi Muglikar, Nico Messikommer, Marco Cannici, Davide Scaramuzza |
ArXiv | 2025 | π· | Paper | ||
| Video Desnower: An Adaptive Feature Fusion Understanding Video Desnowing Model With Deformable Convolution and KNN Point Cloud Transformer Yuxuan Li, Lin Dai |
2024 | πΉ | Paper | |||
| Msp-former: Multi-scale projection transformer for single image desnowing Sixiang Chen, Tian Ye, Yun Liu, Taodong Liao, Jingxia Jiang, Erkang Chen, Peng Chen |
ICASSP | 2023 | π· | Paper | ||
| Lightweight image de-snowing: A better trade-off between network capacity and performance Zheng Chen, Yiwen Sun, Xiaojun Bi, Jianyu Yue |
2023 | π· | Paper | |||
| SnowMaster: Comprehensive Real-world Image Desnowing via MLLM with Multi-Model Feedback Optimization Jianyu Lai, Sixiang Chen, Yunlong Lin, Tian Ye, Yun Liu, Song Fei, Zhaohu Xing, Hongtao Wu, Weiming Wang, Lei Zhu |
CVPR | 2025 | π· | Paper | ||
| Optimized connections and feature interactions for more efficient single-image desnowing Jiawei Mao, Yuanqi Chang, Xuesong Yin, Binling Nie, Yigang Wang |
2025 | π· | Paper | |||
| Context-aware coarse-to-fine network for single image desnowing Yunrui Cheng, Hao Ren, Rui Zhang, Hong Lu |
Multimed Tools Appl. | 2024 | π· | Paper | ||
| Two-Stage Nighttime Desnowing Diffusion Model Based on Pseudo-Scenario Reconstruction Huajing Li, Bin Wang, ZeKun Chen, Lei Zhang, ShiLi Liang, SiJia Guo |
2024 | π· | Paper | |||
| Video desnowing and deraining via saliency and dual adaptive spatiotemporal filtering Yongji Li, Rui Wu, Zhenhong Jia, Jie Yang, Nikola Kasabov |
Sensors | 2021 | πΉ | Paper | ||
| Uncertainty-driven dynamic degradation perceiving and background modeling for efficient single image desnowing Sixiang Chen, Tian Ye, Chenghao Xue, Haoyu Chen, Yun Liu, Erkang Chen, Lei Zhu |
2023 | π· | Paper | |||
| Exploring Local Sparse Structure Prior for Image Deraining and Desnowing Xin Guo, Xueyang Fu, Zheng-Jun Zha |
2024 | π· | Paper | |||
| RVDNet: a two-stage network for real-world video desnowing with domain adaptation Tianhao Xue, Gang Zhou, Runlin He, Zhong Wang, Juan Chen, Zhenhong Jia |
ICASSP | 2024 | πΉ | Paper | ||
| Slide: Self-supervised lidar de-snowing through reconstruction difficulty Gwangtak Bae, Byungjun Kim, Seongyong Ahn, Jihong Min, Inwook Shim |
ECCV | 2022 | π· | Paper | ||
| FedDeSnowNet: Federated De-snowing Network for LiDAR Point Clouds Zhiyu Fang, Boyang Li, Jiahui Liao, Siheng Ren, Kai Huang |
2024 | π· | Paper | |||
| Image snow removal methods for robotic environment fusion Pengyue LI |
2019 | π· | Paper | |||
| Stacked dense networks for single-image snow removal Pengyue Li, Mengshen Yun, Jiandong Tian, Yandong Tang, Guolin Wang, Chengdong Wu |
2019 | π· | Paper | |||
| LIDAR De-Snow Score (DSS): combining quality and perception metrics for optimised data filtering Pak Hung Chan, Daniel Gummadi, Abu Mohammed Raisuddin, Eren Erdal Aksoy, Valentina Donzella |
2024 | π· | Paper | |||
| Wavelet-Enhanced Desnowing: A Novel Single Image Restoration Approach for Traffic Surveillance under Adverse Weather Conditions Zihan Shen, Yu Xuan, Qingyu Yang |
ArXiv | 2025 | π· | Paper | ||
| Unsupervised Domain Adaptive Learning for Image Desnowing with Real-World Data Jingxu Ren, Gang Zhou, Yusen Zhu, Yangxin Liu, Juan Chen, Zhenhong Jia |
ICIP | 2023 | π· | Paper | ||
| Snow removal in video: A new dataset and a novel method Haoyu Chen, Jingjing Ren, Jinjin Gu, Hongtao Wu, Xuequan Lu, Haoming Cai, Lei Zhu |
ICCV | 2023 | πΉ | Paper | ||
| Deep dense multi-scale network for snow removal using semantic and depth priors Kaihao Zhang, Rongqing Li, Yanjiang Yu, Wenhan Luo, Changsheng Li |
TIP | 2021 | π· | Paper | ||
| Deraining and Desnowing Algorithm on Adaptive Tolerance and Dual-tree Complex Wavelet Fusion Jingfeng Zang, Ningxue Xu, Rui Liu, Yuhuan Shi |
2020 | π· | Paper | |||
| Feature Fusion Attention Network with CycleGAN for Image Dehazing, De-Snowing and De-Raining Akshat Jain |
ArXiv | 2025 | π· | Paper | ||
| Stereo video deraining and desnowing based on spatiotemporal frame warping Jin-Hwan Kim, Jae-Young Sim, Chang-Su Kim |
ICIP | 2014 | πΉ | Paper | ||
| Desnowformer: an effective transformer-based image desnowing network Ting Zhang, Nanfeng Jiang, Junhong Lin, Jielian Lin, Tiesong Zhao |
2022 | π· | Paper | |||
| Star-Net: Improving Single Image Desnowing Model With More Efficient Connection and Diverse Feature Interaction Jiawei Mao, Yuanqi Chang, Xuesong Yin, Binling Nie |
ArXiv | 2303 | π· | Paper | ||
| Check for updates Lidar De-snowing Method with Density and Intensity Fusion |
2023 | π· | Paper | |||
| Singleβimage snow removal algorithm based on generative adversarial networks Zhijia Zhang, Sinan Wu, Shixian Wang |
2023 | π· | Paper | |||
| Degradation-adaptive neural network for jointly single image dehazing and desnowing Erkang Chen, Sixiang Chen, Tian Ye, Yun Liu |
2024 | π· | Paper | |||
| Thermal characterisation of electroconductive layers for anti-icing and de-snowing applications on roads P. Leiva-Padilla, F. Moreno-Navarro, G. R. Iglesias, M. C. Rubio-Gamez |
2022 | π· | Paper | |||
| Snowed autoencoders are efficient snow removers Yifan Liu, Jincai Chen, Ping Lu, Chuanbo Zhu, Yugen Jian, Chao Sun, Han Liang |
2023 | π· | Paper | |||
| Rain and Snow Removal Jiandong Tian |
2021 | π· | Paper | |||
| Single image rain/snow removal using distortion type information Hamidreza Fazlali, Shahram Shirani, Michael Bradford, Thia Kirubarajan |
Multimed Tools Appl. | 2022 | π· | Paper | ||
| SnowSTNet: A Spatial-Temporal LiDAR Point Cloud Denoising Network for Autonomous Driving in Snowy Weather Yida Li, Xinyuan Yan, He Huang, Yu Liang, Yidan Zhang, Junxing Yang |
2025 | π· | Paper | |||
| Denoising framework based on multiframe continuous point clouds for autonomous driving LiDAR in snowy weather Xinyuan Yan, Junxing Yang, Xinyu Zhu, Yu Liang, He Huang |
2024 | π· | Paper | |||
| Cross-Stitched Multi-task Dual Recursive Networks for Unified Single Image Deraining and Desnowing Sotiris Karavarsamis, Alexandros Doumanoglou, Konstantinos Konstantoudakis, Dimitrios Zarpalas |
2022 | π· | Paper | |||
| Adaptive two-stage filter for de-snowing LiDAR point clouds Minh-Hai Le, Ching-Hwa Cheng, Don-Gey Liu, Thanh-Tuan Nguyen |
2022 | π· | Paper | |||
| Ultra-efficient and ultra-rapid solar cell de-icing and de-snowing Siavash Khodakarami, Longnan Li, Nenad Miljkovic |
SPIE | 2021 | π· | Paper | ||
| Single Image Desnow Based on Vision Transformer and Conditional Generative Adversarial Network for Internet of Vehicles. Bingcai Wei, Di Wang, Zhuang Wang, Liye Zhang |
2023 | π· | Paper | |||
| Weatherstream: Light transport automation of single image deweathering Howard Zhang, Yunhao Ba, Ethan Yang, Varan Mehra, Blake Gella, Akira Suzuki, Arnold Pfahnl, Chethan Chinder Chandrappa, Alex Wong, Achuta Kadambi |
CVPR | 2023 | π· | Paper | ||
| Parameter-efficient fine-tuning for single image snow removal Xinwei Dai, Yuanbo Zhou, Xintao Qiu, Hui Tang, Tong Tong |
2025 | π· | Paper | |||
| Snow removal for LiDAR point clouds with spatio-temporal conditional random fields Weimin Wang, Ting Yang, Yu Du, Yu Liu |
2023 | π· | Paper | |||
| Desnow-Gnn: Spatiotemporal Graph Neural Network for Robust Lidar Point Cloud Denoising in Adverse Weather Lezhi Liao, Xiao Ding, Kun Zhu, Liang Mei, Haiyan OU |
5364 | π· | Paper | |||
| SnowMamba: Achieving More Precise Snow Removal with Mamba Guoqiang Wang, Yanyun Zhou, Fei Shi, Zhenhong Jia |
2025 | π· | Paper | |||
| Video Desnowing Algorithm Based on Multi-Channel Fusion and Group Sparse Coding |
2023 | πΉ | Paper | |||
| Beyond the snowfall: Enhancing snowy day object detection through progressive restoration and multi-feature fusion Zhong Wang, Gang Zhou, Jing Ma, Tianhao Xue, Zhenhong Jia |
ICASSP | 2024 | π· | Paper | ||
| A simulation computation of twist of De-Snowing electric wires due to snow accretion |
1976 | π· | Paper | |||
| Restoring snow-degraded single images with wavelet in vision transformer Obinna Agbodike, Jenhui Chen |
2023 | π· | Paper | |||
| SnowTextNet: Detection-Guided Restoration Dual-Branch Network for Text Detection in Snowy Scenes Xinyi Chen, Gang Zhou, Li Zhang, Zhenhong Jia |
2025 | π· | Paper | |||
| How Hard Is Snow? A Paired Domain Adaptation Dataset for Clear and Snowy Weather: CADC+ Mei Qi Tang, Sean Sedwards, Chengjie Huang, Krzysztof Czarnecki |
ArXiv | 2025 | π· | Paper | ||
| Restoring vision in adverse weather conditions with patch-based denoising diffusion models Ozan Γzdenizci, Robert Legenstein |
TPAMI | 2023 | π· | Paper | ||
| Simulating Marine Snow Images: Pipeline, Data Set, and Benchmark Yiqing Huang, Tianshun Han, Haoru Zhao, Yanyan Liang, Jun Wan, Sergio Escalera, Haiyong Zheng |
2025 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| All in One Bad Weather Removal Using Architectural Search Ruoteng Li, Robby T. Tan, Loong-Fah Cheong |
CVPR | 2020 | π· | Paper | ||
| Interactive (de) weathering of an image using physical models |
2003 | π· | Paper | |||
| Weatherstream: Light transport automation of single image deweathering Howard Zhang, Yunhao Ba, Ethan Yang, Varan Mehra, Blake Gella, Akira Suzuki, Arnold Pfahnl, Chethan Chinder Chandrappa, Alex Wong, Achuta Kadambi |
CVPR | 2023 | π· | Paper | ||
| Learning real-world image de-weathering with imperfect supervision Xiaohui Liu, Zhilu Zhang, Xiaohe Wu, Chaoyu Feng, Xiaotao Wang, Lei Lei, Wangmeng Zuo |
AAAI | 2024 | π· | Paper | ||
| Residual deformable convolution for better image de-weathering Huikai Liu, Ao Zhang, Wenqian Zhu, Bin Fu, Bingjian Ding, Shengwu Xiong |
PR | 2024 | π· | Paper | ||
| Automatic image de-weathering using physical model and maximum entropy Xin Wang, Zhenmin Tang |
2008 | π· | Paper | |||
| Review on state of art image enhancement and restoration methods for a vision based driver assistance system with De-weathering Achala Chathuranga Aponso, Naomi Krishnarajah |
2011 | π· | Paper | |||
| Pseudo-Label Guided Real-World Image De-weathering: A Learning Framework with Imperfect Supervision Heming Xu, Xiaohui Liu, Zhilu Zhang, Hongzhi Zhang, Xiaohe Wu, Wangmeng Zuo |
ArXiv | 2025 | π· | Paper | ||
| Highlights on weathering effects: Improving the appearance modeling of weathering effects on images Djalma Bandeira, Marcelo Walter |
Vis Comput | 2010 | π· | Paper | ||
| Fast single image and video deweathering using look-up-table approach Apurva Kumari, Subhendu Kumar Sahoo |
2015 | πΉ | Paper | |||
| Automatic image de-weathering using curvelet-based vanishing point detection |
2007 | π· | Paper | |||
| Image de-weathering for road based on physical model Yuhui Zhu, Bin Fang, Huiqing Zhang |
2009 | π· | Paper | |||
| Gpu-accelerated real-time surveillance de-weathering |
2013 | π· | Paper | |||
| Real time image and video deweathering: The future prospects and possibilities Apurva Kumari, Subhendu Kumar Sahoo |
2016 | πΉ | Paper | |||
| A hybrid approach for a vision based driver assistance system with de-weathering Achala Chathuranga Aponso, Naomi Krishnarajah |
2012 | π· | Paper | |||
| Meteorological Normalization or Deweathering for Predicting Air Pollutant Concentration: Pitfalls and Limitations Valentino PetriΔ, Mario LovriΔ, Bernhard C. Geiger |
2024 | π· | Paper | |||
| Significant changes in chemistry of fine particles in wintertime Beijing from 2007 to 2017: impact of clean air actions Yangmei Zhang, Tuan Van Vu, Junying Sun, Jianjun He, Xiaojing Shen, Weili Lin, Xiaoye Zhang, Junting Zhong, Wenkang Gao, Yaqiang Wang, Tzung May Fu, Yaping Ma, Weijun Li, Zongbo Shi |
2019 | π· | Paper | |||
| A Review on Deweathering Methods: Fog & Haze Removal |
2016 | π· | Paper | |||
| Deep learning-based weather image recognition Li-Wei Kang, Ke-Lin Chou, Ru-Hong Fu |
2018 | π· | Paper | |||
| Adverse weather removal with codebook priors Tian Ye, Sixiang Chen, Jinbin Bai, Jun Shi, Chenghao Xue, Jingxia Jiang, Junjie Yin, Erkang Chen, Yun Liu |
ICCV | 2023 | π· | Paper | ||
| Language-driven all-in-one adverse weather removal Hao Yang, Liyuan Pan, Yan Yang, Wei Liang |
CVPR | 2024 | π· | Paper | ||
| Learning multiple adverse weather removal via two-stage knowledge learning and multi-contrastive regularization: Toward a unified model Wei-Ting Chen, Zhi-Kai Huang, Cheng-Che Tsai, Hao-Hsiang Yang, Jian-Jiun Ding, Sy-Yen Kuo |
CVPR | 2022 | π· | Paper | ||
| Exploring the application of large-scale pre-trained models on adverse weather removal Zhentao Tan, Yue Wu, Qiankun Liu, Qi Chu, Le Lu, Jieping Ye, Nenghai Yu |
TIP | 2024 | π· | Paper | ||
| Mowe: mixture of weather experts for multiple adverse weather removal |
2023 | π· | Paper | |||
| Learning weather-general and weather-specific features for image restoration under multiple adverse weather conditions Yurui Zhu, Tianyu Wang, Xueyang Fu, Xuanyu Yang, Xin Guo, Jifeng Dai, Yu Qiao, Xiaowei Hu |
CVPR | 2023 | π· | Paper | ||
| Transweather: Transformer-based restoration of images degraded by adverse weather conditions Jeya Maria Jose Valanarasu, Rajeev Yasarla, Vishal M. Patel |
CVPR | 2022 | π· | Paper | ||
| Continuous adverse weather removal via degradation-aware distillation Xin Lu, Jie Xiao, Yurui Zhu, Xueyang Fu |
CVPR | 2025 | π· | Paper | ||
| DRR: A new method for multiple adverse weather removal Zixuan Li, Fang Long, Wenkang Su, Yuan-Gen Wang, Qingxiao Guan, Lei Cai |
2025 | π· | Paper | |||
| Image all-in-one adverse weather removal via dynamic model weights generation Yecong Wan, Mingwen Shao, Yuanshuo Cheng, Wangmeng Zuo |
2024 | π· | Paper | |||
| Always clear days: Degradation type and severity aware all-in-one adverse weather removal Yu-Wei Chen, Soo-Chang Pei |
2025 | π· | Paper | |||
| Continual all-in-one adverse weather removal with knowledge replay on a unified network structure De Cheng, Yanling Ji, Dong Gong, Yan Li, Nannan Wang, Junwei Han, Dingwen Zhang |
2024 | π· | Paper | |||
| CMAWRNet: Multiple Adverse Weather Removal via a Unified Quaternion Neural Architecture Vladimir Frants, Sos Agaian, Karen Panetta, Peter Huang |
ArXiv | 2025 | π· | Paper | ||
| Genuine knowledge from practice: Diffusion test-time adaptation for video adverse weather removal Yijun Yang, Hongtao Wu, Angelica I. Aviles-Rivero, Yulun Zhang, Jing Qin, Lei Zhu |
CVPR | 2024 | πΉ | Paper | ||
| Rethinking all-in-one adverse weather removal for object detection Yufeng Li, Jiayu Chen, Chuanlong Xie, Hongming Chen |
2024 | π· | Paper | |||
| SemiDDM-Weather: A Semi-supervised Learning Framework for All-in-one Adverse Weather Removal Fang Long, Wenkang Su, Zixuan Li, Lei Cai, Mingjie Li, Yuan-Gen Wang, Xiaochun Cao |
ArXiv | 2024 | π· | Paper | ||
| Framework for generation and removal of multiple types of adverse weather from driving scene images Hanting Yang, Alexander Carballo, Yuxiao Zhang, Kazuya Takeda |
Sensors | 2023 | π· | Paper | ||
| Robust Adverse Weather Removal via Spectral-based Spatial Grouping Yuhwan Jeong, Yunseo Yang, Youngho Yoon, Kuk-Jin Yoon |
ArXiv | 2507 | π· | Paper | ||
| Multimodal prompt state space models for unified adverse weather removal Pengyue Li, Wentao Li, Jiandong Tian, Yandong Tang |
2025 | π· | Paper | |||
| Multiple Adverse Weather Removal Using Masked-Based Pre-Training and Dual-Pooling Adaptive Convolution Shugo Yamashita, Masaaki Ikehara |
2024 | π· | Paper | |||
| Video adverse-weather-component suppression network via weather messenger and adversarial backpropagation Yijun Yang, Angelica I. Aviles-Rivero, Huazhu Fu, Ye Liu, Weiming Wang, Lei Zhu |
ICCV | 2023 | πΉ | Paper | ||
| All in one bad weather removal using architectural search Ruoteng Li, Robby T. Tan, Loong-Fah Cheong |
CVPR | 2020 | π· | Paper | ||
| Decoupling degradation and content processing for adverse weather image restoration Xi Wang, Xueyang Fu, Peng-Tao Jiang, Jie Huang, Mi Zhou, Bo Li, Zheng-Jun Zha |
ArXiv | 2023 | π· | Paper | ||
| WM-MoE: Weather-aware multi-scale mixture-of-experts for blind adverse weather removal Yulin Luo, Rui Zhao, Xiaobao Wei, Jinwei Chen, Yijie Lu, Shenghao Xie, Tianyu Wang, Ruiqin Xiong, Ming Lu, Shanghang Zhang |
ArXiv | 2023 | π· | Paper | ||
| Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removal Rongxin Liao, Feng Li, Yanyan Wei, Zenglin Shi, Le Zhang, Huihui Bai, Meng Wang |
ArXiv | 2025 | π· | Paper | ||
| All-in-one adverse weather removal via dual state space-based diffusion model with degradation-aware guidance Dirui Xie, Xiaofang Hu, Yue Zhou, Shukai Duan |
PR | 2026 | π· | Paper | ||
| RestoreCUFormer: Transformers to Make Strong Encoders via Two-stage Knowledge Learning For Multiple Adverse Weather Removal Jianping Li, Zhihao Wang, Jincheng Wan, Huaiwei Si, Xiang Wang, Guozhen Tan |
2024 | π· | Paper | |||
| Learning to remove bad weather: towards robust visual perception for self-driving Younkwan Lee, Yechan Kim, Jongmin Yu, Moongu Jeon |
2022 | π· | Paper | |||
| Restoring images in adverse weather conditions via histogram transformer Shangquan Sun, Wenqi Ren, Xinwei Gao, Rui Wang, Xiaochun Cao |
ECCV | 2024 | π· | Paper | ||
| Removing Multiple Hybrid Adverse Weather in Video via a Unified Model Yecong Wan, Mingwen Shao, Yuanshuo Cheng, Jun Shu, Shuigen Wang |
ArXiv | 2025 | πΉ | Paper | ||
| WeatherClean: An Image Restoration Algorithm for UAV-Based Railway Inspection in Adverse Weather Kewen Wang, Shaobing Yang, Zexuan Zhang, Zhipeng Wang, Limin Jia, Mengwei Li, Shengjia Yu |
Sensors | 2025 | π· | Paper | ||
| Low-rank adaptation-based all-weather removal for autonomous navigation Sudarshan Rajagopalan, Vishal M. Patel |
ArXiv | 2024 | π· | Paper | ||
| TAP: Parameter-efficient Task-Aware Prompting for Adverse Weather Removal Hanting Wang, Shengpeng Ji, Shulei Wang, Hai Huang, Xiao Jin, Qifei Zhang, Tao Jin |
ArXiv | 2025 | π· | Paper | ||
| Point cloud processing under adverse weather: a survey of datasets, enhancement, and denoising methods Zongwen Gu, Zhizhou Wu, Chi Zhang, Yunyi Liang |
2025 | π· | Paper | |||
| DDCNet: Advanced Decoupling of Degradation and Content for Adverse Weather Image Restoration Xi Wang, Xueyang Fu, Yurui Zhu, Zheng-Jun Zha |
2025 | π· | Paper | |||
| Multiple adverse weather removal using adversarial and contrastive learning Yuanfan Zhang, Jinghua Wang, Liang Hu |
2023 | π· | Paper | |||
| ART-SS: an adaptive rejection technique for semi-supervised restoration for adverse weather-affected images Rajeev Yasarla, Carey E. Priebe, Vishal M. Patel |
ECCV | 2022 | π· | Paper | ||
| Restoring vision in adverse weather conditions with patch-based denoising diffusion models Ozan Γzdenizci, Robert Legenstein |
TPAMI | 2023 | π· | Paper | ||
| 4denoisenet: Adverse weather denoising from adjacent point clouds Alvari Seppanen, Risto Ojala, Kari Tammi |
2022 | π· | Paper | |||
| Combating bad weather part i: Rain removal from video Sudipta Mukhopadhyay, Abhishek Kumar Tripathi |
2014 | πΉ | Paper | |||
| Allweather-net: Unified image enhancement for autonomous driving under adverse weather and low-light conditions Chenghao Qian, Mahdi Rezaei, Saeed Anwar, Wenjing Li, Tanveer Hussain, Mohsen Azarmi, Wei Wang |
PR | 2024 | π· | Paper | ||
| A Review of Unmanned Visual Target Detection in Adverse Weather Yifei Song, Yanfeng Lu |
2025 | π· | Paper | |||
| Disentangled bad weather removal gan for pedestrian detection Hanting Yang, Alexander Carballo, Kazuya Takeda |
2022 | π· | Paper | |||
| Learning to Restore Arbitrary Hybrid adverse weather Conditions in one go Yecong Wan, Mingwen Shao, Yuanshuo Cheng, Yuexian Liu, Zhiyuan Bao |
PR | 2025 | π· | Paper | ||
| Analysis of adverse weather for excusable delays Long D. Nguyen, Jax Kneppers, Borja GarcΓa de Soto, William Ibbs |
2010 | π· | Paper | |||
| Current and future approaches to wet weather flow management: A review Paige E. Peters, Daniel H. Zitomer |
2021 | π· | Paper | |||
| Towards real-world adverse weather image restoration: Enhancing clearness and semantics with vision-language models Jiaqi Xu, Mengyang Wu, Xiaowei Hu, Chi-Wing Fu, Qi Dou, Pheng-Ann Heng |
ECCV | 2024 | π· | Paper | ||
| Multi-weather city: Adverse weather stacking for autonomous driving Valentina MuΘat, Ivan Fursa, Paul Newman, Fabio Cuzzolin, Andrew Bradley |
ICCV | 2021 | π· | Paper | ||
| Weathergs: 3d scene reconstruction in adverse weather conditions via gaussian splatting Chenghao Qian, Yuhu Guo, Wenjing Li, Gustav Markkula |
ArXiv | 2412 | π· | Paper | ||
| Study of Filtering the Weather Adverse Effects to Object Detection S. Shtekhin, D. Karachev, A. Stadnik |
2024 | π· | Paper | |||
| Learning with confidence the likelihood of flight diversion due to adverse weather at destination Ramon Dalmau, Gilles Gawinowski |
2023 | π· | Paper | |||
| β¦ Encoder and Decoder-Based Transformer Fusion with Deep Residual Attention for Restoration of Degraded Images and Clear Visualization in Adverse Weather β¦ Sahadeb Shit, Bappadittya Roy, Dibyendu Kumar Das, Dip Narayan Ray |
2024 | π· | Paper | |||
| Cfmw: Cross-modality fusion mamba for multispectral object detection under adverse weather conditions Haoyuan Li, Qi Hu, Binjia Zhou, You Yao, Jiacheng Lin, Kailun Yang, Peng Chen |
ArXiv | 2404 | π· | Paper | ||
| Framework of degraded image restoration and simultaneous localization and mapping for multiple bad weather conditions Yunlong Dong, Wei Guo, Mantian Li, Fusheng Zha, Bing Shao, Lining Sun |
OE | 2023 | π· | Paper | ||
| Problems related to the operation of autonomous vehicles in adverse weather conditions MichaΕ Brzozowski, Krzysztof Parczewski |
2023 | π· | Paper | |||
| TANet: Triplet attention network for all-in-one adverse weather image restoration Hsing-Hua Wang, Fu-Jen Tsai, Yen-Yu Lin, Chia-Wen Lin |
ACCV | 2024 | π· | Paper | ||
| Power Line Aerial Image Restoration Under Adverse Weather: Datasets and Baselines Sai Yang, Bin Hu, Bojun Zhou, Fan Liu, Xiaoxin Wu, Xinsong Zhang, Juping Gu, Jun Zhou |
2025 | π· | Paper | |||
| Unified multi-weather visibility restoration Ashutosh Kulkarni, Prashant W. Patil, Subrahmanyam Murala, Sunil Gupta |
2022 | π· | Paper | |||
| Degradation type-aware image restoration for effective object detection in adverse weather Xiaochen Huang, Xiaofeng Wang, Qizhi Teng, Xiaohai He, Honggang Chen |
Sensors | 2024 | π· | Paper | ||
| Da-raw: Domain adaptive object detection for real-world adverse weather conditions Minsik Jeon, Junwon Seo, Jihong Min |
ICRA | 2024 | π· | Paper | ||
| Cnn-based lidar point cloud de-noising in adverse weather Robin Heinzler, Florian Piewak, Philipp Schindler, Wilhelm Stork |
2020 | π· | Paper | |||
| Let it snow: On the synthesis of adverse weather image data Thomas Rothmeier, Werner Huber |
2021 | π· | Paper | |||
| DS-Diff: a dual-stage network with degradation-aware and semantic-aware for adverse weather removal based on diffusion models Qian Zhang, Shasha Li, Mingwen Shao |
Multimed Tools Appl. | 2025 | π· | Paper | ||
| AdverseNet: A Unified LiDAR Point Cloud Denoising Network for Autonomous Driving in Adverse Weather |
2025 | π· | Paper | |||
| Contrast restoration of weather degraded images Srinivasa G. Narasimhan, Shree K. Nayar |
2003 | π· | Paper | |||
| Teaching tailored to talent: Adverse weather restoration via prompt pool and depth-anything constraint Sixiang Chen, Tian Ye, Kai Zhang, Zhaohu Xing, Yunlong Lin, Lei Zhu |
ECCV | 2024 | π· | Paper | ||
| Enhancing robustness of weather removal: preprocessing-based defense against adversarial attacks Vladimir A. Frants, Sos S. Agaian |
SPIE | 2024 | π· | Paper | ||
| Survey on lidar perception in adverse weather conditions Mariella Dreissig, Dominik Scheuble, Florian Piewak, Joschka Boedecker |
2023 | π· | Paper | |||
| Gridformer: Residual dense transformer with grid structure for image restoration in adverse weather conditions Tao Wang, Kaihao Zhang, Ziqian Shao, Wenhan Luo, Bjorn Stenger, Tong Lu, Tae-Kyun Kim, Wei Liu, Hongdong Li |
IJCV | 2024 | π· | Paper | ||
| Vehicle detection and tracking in adverse weather using a deep learning framework M. Hassaballah, Mourad A. Kenk, Khan Muhammad, Shervin Minaee |
2020 | π· | Paper | |||
| Rethinking LiDAR object detection in adverse weather conditions Teja Vattem, George Sebastian, Luka Lukic |
ICRA | 2022 | π· | Paper | ||
| Visual quality enhancement of images under adverse weather conditions Jashojit Mukhtarjee, K Praveen, Venugopala Madumbu |
2018 | π· | Paper | |||
| Worsening perception: Real-time degradation of autonomous vehicle perception performance for simulation of adverse weather conditions Ivan Fursa, Elias Fandi, Valentina Musat, Jacob Culley, Enric Gil, Izzeddin Teeti, Louise Bilous, Isaac Vander Sluis, Alexander Rast, Andrew Bradley |
ArXiv | 2021 | π· | Paper | ||
| Depth-aware blind image decomposition for real-world adverse weather recovery Chao Wang, Zhedong Zheng, Ruijie Quan, Yi Yang |
ECCV | 2024 | π· | Paper | ||
| Robust object detection in challenging weather conditions Himanshu Gupta, Oleksandr Kotlyar, Henrik Andreasson, Achim J. Lilienthal |
WACV | 2024 | π· | Paper | ||
| Gradient-Guided Parameter Mask for Multi-Scenario Image Restoration Under Adverse Weather Jilong Guo, Haobo Yang, Mo Zhou, Xinyu Zhang |
ArXiv | 2024 | π· | Paper | ||
| Wavelet-Enhanced Desnowing: A Novel Single Image Restoration Approach for Traffic Surveillance under Adverse Weather Conditions Zihan Shen, Yu Xuan, Qingyu Yang |
ArXiv | 2025 | π· | Paper | ||
| Object Detection in Adverse Weather Conditions using Machine Learning Manish Kumar, Anup Lal Yadav, Abhilaksh Arora, Arnab Deb |
2023 | π· | Paper | |||
| Weather removal with a lightweight quaternion Chebyshev neural network Vladimir A. Frants, Sos Agaian |
SPIE | 2023 | π· | Paper | ||
| Q-KAN: enhancing robustness of weather removal: preprocessing-based defense against adversarial attacks Vladimir A. Franc, Sos Agaian |
SPIE | 2025 | π· | Paper | ||
| MODEM: A Morton-Order Degradation Estimation Mechanism for Adverse Weather Image Recovery Hainuo Wang, Qiming Hu, Xiaojie Guo |
ArXiv | 2025 | π· | Paper | ||
| Perception methods for adverse weather based on vehicle infrastructure cooperation system: A review Jizhao Wang, Zhizhou Wu, Yunyi Liang, Jinjun Tang, Huimiao Chen |
Sensors | 2024 | π· | Paper | ||
| ARODNet: adaptive rain image enhancement object detection network for autonomous driving in adverse weather conditions Yongsheng Qiu, Yuanyao Lu, Yuantao Wang, Haiyang Jiang |
OE | 2023 | π· | Paper | ||
| AWRaCLe: All-weather image restoration using visual in-context learning Sudarshan Rajagopalan, Vishal M. Patel |
AAAI | 2025 | π· | Paper | ||
| Dsor: A scalable statistical filter for removing falling snow from lidar point clouds in severe winter weather Akhil Kurup, Jeremy Bos |
ArXiv | 2021 | π· | Paper | ||
| The impact of adverse weather conditions on autonomous vehicles: How rain, snow, fog, and hail affect the performance of a self-driving car Shizhe Zang, Ming Ding, David Smith, Paul Tyler, Thierry Rakotoarivelo, Mohamed Ali Kaafar |
2019 | π· | Paper | |||
| Prompt-guided and degradation prior supervised transformer for adverse weather image restoration Weihan Liu, Mingwen Shao, Lingzhuang Meng, Yuanjian Qiao, Zhiyuan Bao |
Appl. Intell. | 2025 | π· | Paper | ||
| Adverse weather target detection algorithm based on adaptive color levels and improved YOLOv5 Jiale Yao, Xiangsuo Fan, Bing Li, Wenlin Qin |
Sensors | 2022 | π· | Paper | ||
| Test-time Adaptation for Real-World Video Adverse Weather Restoration with Meta Batch Normalization Jinliang Liu, Zongxin Yang |
TCSVT | 2025 | πΉ | Paper | ||
| Restoring images captured in arbitrary hybrid adverse weather conditions in one go Ye-Cong Wan, Ming-Wen Shao, Yuan-Shuo Cheng, Yue-Xian Liu, Zhi-Yuan Bao |
ArXiv | 2023 | π· | Paper | ||
| Unifying Physically-Informed Weather Priors in A Single Model for Image Restoration Across Multiple Adverse Weather Conditions Jiaqi Xu, Xiaowei Hu, Lei Zhu, Pheng-Ann Heng |
TCSVT | 2025 | π· | Paper | ||
| Perception-friendly video enhancement for autonomous driving under adverse weather conditions Younkwan Lee, Yeongmin Ko, Yechan Kim, Moongu Jeon |
ICRA | 2022 | πΉ | Paper | ||
| AdWeatherNet: Adverse Weather Denoising with Point Cloud Spatiotemporal Attention Haozheng Han, Dongyu Du, Jie Luo, Xin Jin |
2024 | π· | Paper | |||
| Adaptive enhancement of spatial information in adverse weather Mohammad Shabaz, Mukesh Soni |
2024 | π· | Paper | |||
| WRRT-DETR: weather-robust RT-DETR for drone-view object detection in adverse weather Bei Liu, Jiangliang Jin, Yihong Zhang, Chen Sun |
Drones | 2025 | π· | Paper | ||
| Rethinking data augmentation for robust lidar semantic segmentation in adverse weather Junsung Park, Kyungmin Kim, Hyunjung Shim |
ECCV | 2024 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Three-Channel Infrared Imaging for Object Detection in Haze Beinan Yu, Yifan Chen, Si-Yuan Cao, Hui-Liang Shen, Junwei Li |
TIM | 2022 | Haze | π· | Paper | |
| Detection-Friendly Dehazing: Object Detection in Real-World Hazy Scenes Chengyang Li; Heng Zhou; Yang Liu; Caidong Yang; Yongqiang Xie; Zhongbo Li |
TPAMI | 2023 | Haze | π· | Paper | |
| Unified Density-Aware Image Dehazing and Object Detection in Real-World Hazy Scenes Zhengxi Zhangβ, Liang Zhaoβ, Yunan Liu, Shanshan Zhang, Jian Yan |
ACCV | 2020 | Haze | π· | Paper | Code |
| HazyDet: Open-Source Benchmark for Drone-View Object Detection with Depth-Cues in Hazy Scenes Changfeng Feng, Zhenyuan Chen, Xiang Li, Chunping Wang, Jian Yang, Ming-Ming Cheng, Yimian Dai, Qiang Fu |
ArXiv | 2024 | Haze | π· π | Paper | Code |
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Curating papers for this section. Contributions welcome |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| DEHRFormer: Real-Time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes Sixiang Chen; Tian Ye; Jun Shi; Yun Liu; JingXia Jiang; Erkang Chen |
ICASSP | 2023 | π«οΈ | π· | Paper | |
| Depth Estimation for Hazy Images Using Deep Learning Laksmita Rahadianti; Fumihiko Sakaue; Jun Sato |
ACPR | 2017 | π«οΈ | π· | Paper | |
| CNN-Based Simultaneous Dehazing and Depth Estimation Byeong-Uk Lee; Kyunghyun Lee; Jean Oh; In So Kweon |
ICRA | 2020 | π«οΈ | π· | Paper | |
| S2DNet: Depth Estimation From Single Image and Sparse Samples Praful Hambarde; Subrahmanyam Murala |
TCI | 2020 | π«οΈ | π· | Paper | |
| Depth-Centric Dehazing and Depth-Estimation from Real-World Hazy Driving Video Junkai Fan, Kun Wang, Zhiqiang Yan, Xiang Chen, Shangbing Gao, Jun Li, Jian Yang |
AAAI | 2025 | π«οΈ | πΉ | Paper | Code |
| Combining semantic scene priors and haze removal for single image depth estimation Ke Wang; Enrique Dunn; Joseph Tighe; Jan-Michael Frahm |
WACV | 2014 | π«οΈ | π· | Paper | |
| Depth Estimation from Single Hazy Images with 2-Phase Training Laksmita Rahadianti; Fumihiko Sakaue; Jun Sato |
ICACSIS | 2020 | π«οΈ | π· | Paper | |
| Progressive dehazing and depth estimation from a single hazy image Jeonghoon Kim, Sungyoon Kim, Changhoon Pyo, Hyeongmyeon Kim, Changhoon Yi |
IEIE SPC | 2022 | π«οΈ | π· | Paper | |
| Image-Based PM2.5 Estimation and its Application on Depth Estimation Jian Ma; Kun Li; Yahong Han; Pufeng Du; Jingyu Yang |
ICASSP | 2018 | π«οΈ | π· | Paper | |
| Robust Depth Estimation in Foggy Environments Combining RGB Images and mmWave Radar Mengchen Xiong; Xiao Xu; Dong Yang; Eckehard Steinbach |
ISM | 2022 | π«οΈ | π· | Paper | |
| FoggyDepth: Leveraging Channel Frequency and Non-Local Features for Depth Estimation in Fog Mengjiao Shen; Liuyi Wang; Xianyou Zhong; Chengju Liu; Qijun Chen |
TCSVT | 2025 | π«οΈ | π· | Paper | |
| Fog density estimation and image defogging based on surrogate modeling for optical depth Yutong Jiang; Changming Sun; Yu Zhao; Li Yang |
TIP | 2017 | π«οΈ | π· | Paper | |
| Example based depth from fog Kristofor B. Gibson; Serge J. Belongie; Truong Q. Nguyen |
ICIP | 2013 | π«οΈ | π· | Paper | |
| An enhanced window-variant dark channel prior for depth estimation using single foggy image Jie Chen; Lap-Pui Chau |
ICIP | 2013 | π«οΈ | π· | Paper | |
| Self-supervised monocular depth estimation in fog Bo Taoβ , Jiaxin Huβ , Du Jiang, Gongfa Li, Baojia Chen, Xinbo Qian |
OE | 2022 | π«οΈ | π· | Paper | Code |
| Estimating Fog Parameters From an Image Sequence Using Non-Linear Optimisation Yining Ding, Andrew M. Wallace, Sen Wang |
WACV | 2024 | π«οΈ | π· | Paper | |
| Factorizing Scene Albedo and Depth from a Single Foggy Image Louis Kratz; Ko Nishino |
ICCV | 2009 | π«οΈ | π· | Paper | |
| Self-supervised Monocular Depth Estimation: Let's Talk About The Weather Kieran Saunders, George Vogiatzis, Luis J. Manso |
ICCV | 2023 | π«οΈπ§οΈβοΈ | π· | Paper | Code |
| Unsupervised Monocular Depth Estimation for Foggy Images with Domain Separation and Self-Depth Domain Conversion Fuyang Liu, Jianjun Li |
CVM | 2025 | π«οΈ | π· | Paper | |
| Depth from phasor distortions in fog Takeshi Muraji, Kenichiro Tanaka, Takuya Funatomi, Yasuhiro Mukaigawa |
Optics Express | 2019 | π«οΈ | π· | Paper | Code |
| Gated2Gated: Self-Supervised Depth Estimation from Gated Images Amanpreet Walia, Stefanie Walz, Mario Bijelic, Fahim Mannan, Frank Julca-Aguilar, Michael Langer, Werner Ritter, Felix Heide |
CVPR | 2022 | π«οΈβοΈ | π· | Paper | Code |
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
| Robust Monocular Depth Estimation under Challenging Conditions Stefano Gasperini, Nils Morbitzer, HyunJun Jung, Nassir Navab, Federico Tombari |
ICCV | 2023 | π§οΈπ | π· | Paper | Code |
| Empirical Study: Monocular Depth Estimation from RGB, NIR, Thermal Image in Adverse Weather Conditions Ukcheol Shin; Soonmin Hwang; Jean Oh |
ICTC | 2023 | π§οΈβοΈπ | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Curating papers for this section. Contributions welcome |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Dehazing-NeRF: Neural Radiance Fields from Hazy Images Tian Li, LU Li, Wei Wang, Zhangchi Feng |
ArXiv | 2023 | π«οΈ | π· | Paper | Code |
| DehazeNeRF: Multiple Image Haze Removal and 3D Shape Reconstruction using Neural Radiance Fields Wei-Ting Chen, Wang Yifan, Sy-Yen Kuo, Gordon Wetzstein |
3DV | 2024 | π«οΈ | π· | Paper | Code |
| RainyScape: Unsupervised Rainy Scene Reconstruction using Decoupled Neural Rendering Xianqiang Lyu, Hui Liu, Junhui Hou |
MM | 2024 | π§οΈ | π· | Paper | Code |
| DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments Shuhong Liu, Xiang Chen, Hongming Chen, Quanfeng Xu, Mingrui Li |
AAAI | 2025 | π§οΈ | π· | Paper | |
| DerainNeRF: 3D Scene Estimation with Adhesive Waterdrop Removal Yunhao Li, Jing Wu, Lingzhe Zhao, Peidong Liu |
ICRA | 2024 | π§ | π· | Paper | Code |
| Weathergs: 3d scene reconstruction in adverse weather conditions via gaussian splatting Chenghao Qian, Yuhu Guo, Wenjing Li, Gustav Markkula |
ICRA | 2025 | π§οΈβοΈ | π· | Paper | Code |
| ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field Yuan Li, Zhi-Hao Lin, David Forsyth, Jia-Bin Huang, Shenlong Wang |
ICCV | 2023 | π«οΈβοΈ | π· | Paper | Code |
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
| WeatherDiffusion: Weather-Guided Diffusion Model for Forward and Inverse Rendering Yixin Zhu, Zuoliang Zhu, MiloΕ‘ HaΕ‘an, Jian Yang, Jin Xie, Beibei Wang |
ArXiv | 2025 | π«οΈπ§οΈβοΈ | π· | Paper | |
| Physics-Based Rendering for Improving Robustness to Rain Shirsendu Halder; Jean-Francois Lalonde; Raoul De Charette |
ICCV | 2019 | π§οΈ | π· | Paper | Code |
| ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering Andrea Ramazzina, Mario Bijelic, Stefanie Walz, Alessandro Sanvito, Dominik Scheuble, Felix Heide |
ICCV | 2023 | π«οΈ | π· | Paper | Code |
| ClimateGS: Real-Time Climate Simulation with 3D Gaussian Style Transfer Yuezhen Xie, Meiying Zhang, Qi Hao |
ArXiv | 2025 | :snow: | π· | Paper | |
| WeatherEdit: Controllable Weather Editing with 4D Gaussian Field Chenghao Qian, Wenjing Li, Yuhu Guo, Gustav Markkula |
ArXiv | 2025 | π«οΈπ§οΈβοΈ | π· | Paper | Code |
| Dataset / Benchmark | Task | Year | Data | Paper | Code |
|---|---|---|---|---|---|
| D-HAZY | Dehazing | 2016 | π·π | Paper | |
| RESIDE | Dehazing | 2018 | π·π | Paper | Code |
| I-HAZE | Dehazing | 2018 | π·π | Paper | |
| O-HAZE | Dehazing | 2018 | π·π | Paper | |
| NH-HAZE | Dehazing | 2020 | π·π | Paper | |
| Dense-Haze | Dehazing | 2019 | π·π | Paper | |
| HazyDet | Object Detection in Haze | 2024 | π·π | Paper | Code |
If you find this repository useful, please consider citing the survey papers listed above and starring the repository.
Pull requests for missing papers, metadata fixes, broken links, and benchmark updates are welcome. Please keep each entry in the existing table format and prefer official project or author-maintained code links when available.