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Challenge and Dataset on Large-scale Human-centric Video Analysis in Complex Events (HiEve) |
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Challenge and Dataset on Large-scale Human-centric Video Analysis in Complex Events (HiEve) |
| Team Name | MR | AP | JI |
|---|---|---|---|
| first-result |
0.7198 | 0.5890 | 0.4905 | Anonymous submission |
| second-result |
0.7168 | 0.5912 | 0.4932 | Anonymous submission |
| 2nd_submission |
0.7147 | 0.5981 | 0.5026 | Anonymous submission |
| result |
0.7103 | 0.6072 | 0.5157 | Y Tang, B Li, M Liu, et al.. AutoPedestrian: An Automatic Data Augmentation and Loss Function Search Scheme for Pedestrian Detection. In TIP, 2021 |
| RetinaNet (Baseline) |
0.7041 | 0.6082 | 0.4898 | TY Lin, P Goyal, R Girshick, K He. Focal loss for dense object detection. In ICCV, 2017 |
| FasterRCNN (Baseline) |
0.6722 | 0.5935 | 0.5156 | S Ren, K He, R Girshick, et al.. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In NIPS, 2015 |