Multi-Object Tracking on BDD100K (test)
60Mean IDF1SUSHI
Evaluation results
| Method | Links | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SUSHIBackbone=YOLOX-X, Pre-train=COCO2023.11 | 60 | 40.2 | — | — | — | — | 13,626 | — | — | — | — | — | — | 48.2 | — | — | |
| GHOST2022.06 | 57 | 39.5 | 68.9 | 72 | — | — | — | — | — | — | — | — | — | 46.8 | 62.2 | — | |
| GHOSTVenue=CVPR'232024.06 | 57 | 39.5 | 68.9 | 72 | — | — | — | — | — | — | — | — | — | 46.8 | 62.2 | — | |
| GeneralTrack2024.06 | 56.9 | 39.9 | 69.1 | 73.6 | — | — | 14,489 | 21,281 | 3,715 | — | — | — | — | 47.9 | 63.7 | — | |
| ContrasTRBackbone=Swin-L, Pre-train=BDD100K2023.11 | 56.5 | 42.8 | — | — | — | — | 10,793 | — | — | — | — | — | — | 46.1 | — | — | |
| ByteTrack2021.10 | 55.8 | 40.1 | 69.6 | 71.3 | 169,073 | 63,869 | 15,466 | 18,057 | 5,107 | — | — | — | — | — | — | — | |
| ByteTrack2022.06 | 55.8 | 40.1 | 69.6 | 71.3 | — | — | — | — | — | — | — | — | — | — | — | — | |
| ByteTrackDetector=YOLOX-X, Base model=Modified CSP, Pre-trained weights=COCO2022.10 | 55.8 | 40.1 | 69.9 | 71.3 | 169,073 | 63,869 | 15,466 | 18,057 | 5,107 | — | — | — | — | — | — | — | |
| ByteTrackVenue=ECCV'222024.06 | 55.8 | 40.1 | 69.6 | — | — | — | 15,466 | 18,057 | 5,107 | — | — | — | — | — | 71.3 | — | |
| ByteTrackBackbone=YOLOX-X, Pre-train=COCO2023.11 | 55.8 | 40.1 | — | — | — | — | 15,466 | — | — | — | — | — | — | — | — | — | |
| QDTrackDetector=YOLOX-X, Base model=Modified CSP, Pre-trained weights=COCO2022.10 | 55.6 | 42.4 | 68.4 | 73.9 | 154,797 | 89,376 | 14,282 | 19,852 | 3,924 | — | — | — | — | — | — | — | |
| QDTrackDetector=FRCNN, Base model=R50-FPN2022.10 | 54.1 | 38.7 | 66.5 | 74 | 185,773 | 78,068 | 10,098 | 18,167 | 4,635 | — | — | — | — | — | — | — | |
| TETer2022.07 | 53.3 | 37.4 | — | — | — | — | — | — | — | 50.42 | 46.99 | 53.56 | 50.71 | — | — | — | |
| TETerDetector=FRCNN, Base model=R50-FPN2022.10 | 53.3 | 37.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| TETerBackbone=ResNet-50, Pre-train=BDD100K2023.11 | 53.3 | 37.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| QDTrackVenue=CVPR'212024.06 | 52.4 | 35.7 | 64.6 | 72.5 | — | — | 10,790 | 17,353 | 5,167 | — | — | — | — | 41.9 | 60.5 | — | |
| QDTrackBackbone=ResNet-50, Pre-train=BDD100K2023.11 | 52.4 | 35.6 | — | — | — | — | 10,790 | — | — | — | — | — | — | 41.8 | — | — | |
| QDTrack2021.10 | 52.3 | 35.5 | 64.3 | 72.3 | 201,041 | 80,054 | 10,790 | 17,353 | 5,167 | — | — | — | — | — | — | — | |
| QDTrack2022.07 | 52.3 | 35.7 | — | — | — | — | — | — | — | 49.17 | 47.19 | 50.93 | 49.38 | — | — | — | |
| QDTrack2022.06 | 52.3 | 35.5 | 64.3 | 72.3 | — | — | — | — | — | — | — | — | — | — | — | — | |
| QDTrackSplit=test2020.06 | 52.3 | 35.5 | 64.3 | 72.3 | 201,041 | 80,054 | 10,790 | 17,353 | 5,167 | — | — | — | — | — | — | 31.8 | |
| DeepSORT2022.07 | 50.2 | 34 | — | — | — | — | — | — | — | 46.75 | 45.26 | 47.04 | 47.93 | — | — | — | |
| DeepSORTDetector=FRCNN, Base model=R50-FPN2022.10 | 50.2 | 34 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Yu et al.2021.10 | 44.7 | 26.3 | 58.3 | 68.2 | 213,220 | 100,230 | 14,674 | 16,299 | 6,017 | — | — | — | — | — | — | — | |
| Yu et alDetector=FRCNN, Base model=DLA-342022.10 | 44.7 | 26.3 | 58.3 | 68.2 | 213,220 | 100,230 | 14,674 | 16,299 | 6,017 | — | — | — | — | — | — | — | |
| Yu et al.Backbone=ResNet-1012023.11 | 44.7 | 26.3 | — | — | — | — | 14,674 | — | — | — | — | — | — | — | — | — | |
| Yu et al.Split=test2020.06 | 44.7 | 26.3 | 58.3 | 68.2 | 213,220 | 100,230 | 14,674 | 16,299 | 6,017 | — | — | — | — | — | — | 27.9 | |
| madamada2021.10 | 43 | 33.6 | 59.8 | 55.7 | 209,339 | 76,612 | 42,901 | 16,774 | 5,004 | — | — | — | — | — | — | — | |
| madamada2022.10 | 43 | 33.6 | 59.8 | 55.7 | 209,339 | 76,612 | 42,901 | 16,774 | 5,004 | — | — | — | — | — | — | — | |
| madamada2024.06 | 43 | 33.6 | 59.8 | — | — | — | 42,901 | 16,774 | 5,004 | — | — | — | — | — | 55.7 | — | |
| madamadaSplit=test2020.06 | 43 | 33.6 | 59.8 | 55.7 | 209,339 | 76,612 | 42,901 | 16,774 | 5,004 | — | — | — | — | — | — | — | |
| DeepBlueAI2021.10 | 38.7 | 31.6 | 56.9 | 56 | 292,063 | 35,401 | 25,186 | 10,296 | 12,266 | — | — | — | — | — | — | — | |
| DeepBlueAI2022.10 | 38.7 | 31.6 | 56.9 | 56 | 292,063 | 35,401 | 25,186 | 10,296 | 12,266 | — | — | — | — | — | — | — | |
| DeepBlueAl2024.06 | 38.7 | 31.6 | 56.9 | — | — | — | 25,186 | 10,296 | 12,266 | — | — | — | — | — | 56 | — | |
| DeepBlueAISplit=test2020.06 | 38.7 | 31.6 | 56.9 | 56 | 292,063 | 35,401 | 25,186 | 10,296 | 12,266 | — | — | — | — | — | — | — | |
| Yu et al.2022.06 | 26.3 | — | — | 58.3 | — | — | — | — | — | — | — | — | — | 44.7 | 68.2 | — |