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@DiffusionAD

DiffusionAD

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Diffusion AD

🙌 DiffusionAD​​ is a research team ​​focused on fully harnessing​​ the power of ​​diffusion models​​ for autonomous driving systems. Our ​​research interests​​ lie in:

  • ​​Diffusion model with efficient and effective architecture design​​ for ​​​​autonomous driving systems
  • Diffusion-based IL/RL algorithms​​ for ​​generalizable and robust​​ autonomous driving systems
  • ​​Diffusion-based​​ autonomous driving systems (​​Perception-Planning / End-to-End / VLA​​)

Projects:

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  1. Flow-Planner Flow-Planner Public

    [NeurIPS 2025] Official implementation for "Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling"

    Python 185 29

  2. BREEZE BREEZE Public

    Forked from Whiterrrrr/BREEZE

    [NeurIPS 2025] The official implementation of "Towards Robust Zero-Shot Reinforcement Learning"

    Python 4 1

  3. Diffusion-Planner Diffusion-Planner Public

    Forked from ZhengYinan-AIR/Diffusion-Planner

    [ICLR 2025 Oral] The official implementation of "Diffusion-Based Planning for Autonomous Driving with Flexible Guidance"

    Python 2

  4. FISOR FISOR Public

    Forked from ZhengYinan-AIR/FISOR

    [ICLR 2024] The official implementation of "Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model"

    Python 2

  5. Hyper-Diffusion-Planner Hyper-Diffusion-Planner Public

    Forked from ZhengYinan-AIR/Hyper-Diffusion-Planner

    The official implementation of "Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving"

    Python 2 1

  6. DIPOLE DIPOLE Public

    Forked from LRMbbj/DIPOLE

    The official implementation of "Dichotomous Diffusion Policy Optimization"

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