Short name:
LPC_MOT
Detector:
Public
Description:
This approach is devised by Tsinghua University and AIBEE Inc.
Reference:
P. Dai, R. Weng, W. Choi, C. Zhang, Z. He, W. Ding. Learning a Proposal Classifier for Multiple Object tracking. In CVPR (Accepted), 2021.
Last submitted:
July 05, 2020 (4 years ago)
Published:
July 05, 2020 at 09:05:11 CET
Submissions:
2
Project page / code:
Open source:
Yes
Hardware:
GeForce GTX 1080 Ti
Runtime:
0.7 Hz
Benchmark performance:
Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
MOT20 | 56.3 | 62.5 | 49.0 | 424 (34.1) | 313 (25.2) | 11,726 | 213,056 | 58.8 | 96.3 | 52.4 | 45.8 | 54.7 | 81.3 | 48.1 | 78.7 | 82.3 | 2.6 | 1,562 (26.6) | 1,865 (31.7) |
Detailed performance:
Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
MOT20-04 | 75.7 | 75.7 | 59.2 | 356 | 63 | 4,180 | 61,864 | 77.4 | 98.1 | 57.8 | 60.8 | 60.3 | 82.6 | 63.8 | 80.8 | 83.0 | 2.0 | 648 | 670 |
MOT20-06 | 35.3 | 43.2 | 33.3 | 35 | 121 | 3,503 | 81,891 | 38.3 | 93.6 | 37.7 | 29.5 | 39.4 | 78.0 | 30.8 | 75.2 | 80.6 | 3.5 | 499 | 653 |
MOT20-07 | 50.8 | 58.9 | 44.5 | 20 | 29 | 229 | 15,921 | 51.9 | 98.7 | 48.9 | 40.6 | 51.2 | 81.1 | 42.1 | 80.1 | 82.3 | 0.4 | 124 | 138 |
MOT20-08 | 25.8 | 37.4 | 29.4 | 13 | 100 | 3,814 | 53,380 | 31.1 | 86.3 | 37.1 | 23.4 | 39.1 | 74.7 | 24.8 | 68.9 | 79.3 | 4.7 | 291 | 404 |
Raw data: