@inproceedings{bergmann2019tracking,
title={Tracking without bells and whistles},
author={Bergmann, Philipp and Meinhardt, Tim and Leal-Taixe, Laura},
booktitle={Proceedings of the IEEE international conference on computer vision},
pages={941--951},
year={2019}
}We implement Tracktor with independent detector and ReID models. To train a model by yourself, you need to train a detector following here and also train a ReID model. The configs in this folder are basiclly for inference.
Currently we do not support training ReID models. We directly use the ReID model from Tracktor. These missed features will be supported in the future.
The implementations of Tracktor follow the offical practices. In the table below, the result marked with * (the last line) is the offical one. Our implementation outperform it by 4.9 points on MOTA and 3.3 points on IDF1.
| Detector | ReID | Train Set | Test Set | Public | Inf time (fps) | MOTA | IDF1 | FP | FN | IDSw. | Config | Download |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| R50-FasterRCNN-FPN | R50 | half-train | half-val | Y | 3.2 | 57.3 | 63.4 | 1254 | 67091 | 613 | config | detector reid |
| R50-FasterRCNN-FPN | R50 | half-train | half-val | N | 3.1 | 64.1 | 66.5 | 11088 | 45762 | 1224 | config | detector reid |
| R50-FasterRCNN-FPN | R50 | train | train | Y | 3.2 | 69.3 | 69.3 | 4010 | 97918 | 1527 | config | detector reid |
| R50-FasterRCNN-FPN | R50 | train | train | N | 3.1 | 82.1 | 73.4 | 12789 | 44631 | 2988 | config | detector reid |
| R50-FasterRCNN-FPN | R50 | train | test | Y | 3.2 | 61.2 | 58.4 | 8612 | 207628 | 2637 | config | detector reid |
| R50-FasterRCNN-FPN* | R50 | train | test | Y | - | 56.3 | 55.1 | 8866 | 235449 | 1987 | - | - |