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TVMCE Dataset

TV shows MultiCamera Editing

It is the data used in Temporal and Contextual Transformer for Multi-Camera Editing of TV Shows

Download

Check the project website.

Folder structure

Notes:

  • For track selection, we only use frame that its boundary label is 1, since we care where the choice of camera tracks on the shot boundary.
  • For data transfer efficiency, we compress the video file as a .tar, and it requires decompression to use, such as tar -xvf video_0002.tar.
β”œβ”€β”€ TVMCE
β”‚   β”œβ”€β”€ meta
β”‚   β”‚   β”œβ”€β”€ train.json         # Json file used with a sampling stride of 5 frames
β”‚   β”‚   β”œβ”€β”€ test.json          # The structure is the same as the meta/train folder
β”‚   β”œβ”€β”€ train                  # Video frames file with a sampling stride of 5 frames
β”‚   β”‚   β”œβ”€β”€ video_0002         # Video TV Show id
β”‚   β”‚   β”‚   β”œβ”€β”€ output         # Video frames from the final output
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ 18362.jpg
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ ...
β”‚   β”‚   β”‚   β”œβ”€β”€ CAM1           # Video frames from different track
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ 18460.jpg
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ ...
β”‚   β”‚   β”‚   β”œβ”€β”€ CAM2
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ 18460.jpg
β”‚   β”‚   β”‚   β”‚   β”œβ”€β”€ ...
β”‚   β”‚   β”‚   β”œβ”€β”€ ...
β”‚   β”‚   β”œβ”€β”€ video_0003         # Other TV Shows, and the structure is the same as the video_0002 folder
β”‚   β”‚   β”‚   β”œβ”€β”€ ...  
β”‚   β”‚   β”œβ”€β”€ ...
β”‚   β”œβ”€β”€ test                   # The structure is the same as the train folder
β”‚   β”‚   β”œβ”€β”€ video_0000
β”‚   β”‚   β”œβ”€β”€ ...

Details about the label file.

train.json
[
    {
    "videoID"               : program_name,
    "sampleInterval"        : int,              # Different sampling stride
    "startFrame"            : int,              # Start frame of sliding window
    "currentCam"            : camera_namm,      # Camera id of the historical information
    "outputList"            : [framid],         # Temporal frame ids 
    "selectCam"             : camera_namm,      # Camera id of selected
    "CAMFrame"              : int,              # Contextual frame id
    "label"                 : [...],            # Label for whether candidate cameras are selected
    "boundary"              : bool,             # Whether to switch cameras
    "CAMList"               : [...]             # List of candidate cameras
    },
    {...}
]

Citation

@article{rao2022temporal,
  title={Temporal and Contextual Transformer for Multi-Camera Editing of TV Shows},
  author={Rao, Anyi and Jiang, Xuekun and Wang, Sichen and Guo, Yuwei and Liu, Zihao and Dai, Bo and Pang, Long and Wu, Xiaoyu and Lin, Dahua and Jin, Libiao},
  journal={arXiv preprint arXiv:2210.08737},
  year={2022}
}