The Omni-MOT is realistic CARLA based large-scale dataset with over 14M frames for multiple vehicle tracking . The dataset comprises 14M+ frames, 250K tracks, 110 million bounding boxes, three weather conditions, three crowd levels and three camera views in five simulated towns.

[baidu], [google drive is not enough], [dropbox is also not that enough]

The published dataset comprises five-level structures. At the 1st level, we divide this dataset into the training set and the testing set. At the 2nd level, we employ five towns in the CARLA Simulator. At the 3rd level, we put the camera at different viewpoints containing five difficulty ranks. At the 4th level, we simulate different weathers. At the 5th level, we create a different number of cars.

@inproceedings{ShiJie20,
  author = {Shijie Sun, Naveed Aktar, XiangYu Song, Huansheng Song, Ajmal Mian, Mubarak Shah},
  title = {Simultaneous Detection and Tracking with Motion Modelling for Multiple Object Tracking},
  booktitle = {Proceedings of the European conference on computer vision (ECCV)}},
  year = {2020}

@inproceedings{Dosovitskiy17,
  title = {{CARLA}: {An} Open Urban Driving Simulator},
  author = {Alexey Dosovitskiy and German Ros and Felipe Codevilla and Antonio Lopez and Vladlen Koltun},
  booktitle = {Proceedings of the 1st Annual Conference on Robot Learning},
  pages = {1--16},
  year = {2017}
}

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