├── LICENSE
├── README.md
├── eTransCenter_pipeline.png
└── transcenter_mot20_example.gif
/LICENSE:
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1 | TransCenter: Transformers with Dense Representations for Multiple-Object Tracking
2 | Copyright Inria
3 | Year 2022
4 | Contact : yihong.xu@inria.fr
5 |
6 | TransCenter is free software: you can redistribute it and/or modify
7 | it under the terms of the GNU General Public License as published by
8 | the Free Software Foundation, either version 3 of the License, or
9 | (at your option) any later version.
10 |
11 | TransCenter is distributed in the hope that it will be useful,
12 | but WITHOUT ANY WARRANTY; without even the implied warranty of
13 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14 | GNU General Public License for more details.
15 |
16 | You should have received a copy of the GNU General Public License
17 | along with this program, TransCenter. If not, see and the LICENSE file.
18 |
19 | TransCenter has code derived from
20 | (1) Deformable-DETR, https://github.com/fundamentalvision/Deformable-DETR, distributed under Apache License 2.0 2020 fundamentalvision.
21 | (2) tracking_wo_bnw, https://github.com/phil-bergmann/tracking_wo_bnw, distributed under GNU General Public License v3.0 2020 Philipp Bergmann, Tim Meinhardt.
22 | (3) DETR, https://github.com/facebookresearch/detr/, distributed under Apache License 2.0 2020 Facebook.
23 | (4) CenterTrack, https://github.com/xingyizhou/CenterTrack, distributed under MIT License 2020 Xingyi Zhou.
24 | Below you can find the License associated to this CenterTrack software:
25 | --------
26 | MIT License
27 |
28 | Copyright (c) 2020 Xingyi Zhou
29 |
30 | Permission is hereby granted, free of charge, to any person obtaining a copy
31 | of this software and associated documentation files (the "Software"), to deal
32 | in the Software without restriction, including without limitation the rights
33 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
34 | copies of the Software, and to permit persons to whom the Software is
35 | furnished to do so, subject to the following conditions:
36 |
37 | The above copyright notice and this permission notice shall be included in all
38 | copies or substantial portions of the Software.
39 |
40 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
41 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
42 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
43 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
44 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
45 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
46 | SOFTWARE.
47 |
48 | TransCenter uses packages from
49 | (1) DCNv2, https://github.com/CharlesShang/DCNv2, distributed under BSD 3-Clause 2019 Charles Shang.
50 | (2) MultiScaleDeformableAttention, https://github.com/fundamentalvision/Deformable-DETR distributed under Apache-2.0 license 2020 fundamentalvision.
51 |
52 | Below you can find the License associated to this TransCenter software:
53 |
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--------------------------------------------------------------------------------
/README.md:
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1 | ## TransCenter: Transformers with Dense Representations for Multiple-Object Tracking
2 | ## The work is accepted for TPAMI 2022.
3 | ## An update towards a more efficient and powerful TransCenter, TransCenter-Lite! ##
4 |
5 | ## The code for TransCenter and TransCenter-Lite is now available, you can find the code and pretrained models at https://gitlab.inria.fr/robotlearn/TransCenter_official.
6 |
7 | **TransCenter: Transformers with Dense Representations for Multiple-Object Tracking**
8 | [Yihong Xu](https://team.inria.fr/robotlearn/team-members/yihong-xu/), [Yutong Ban](https://people.csail.mit.edu/yban/index.html), [Guillaume Delorme](https://team.inria.fr/robotlearn/team-members/guillaume-delorme/), [Chuang Gan](https://people.csail.mit.edu/ganchuang/), [Daniela Rus](http://danielarus.csail.mit.edu/), [Xavier Alameda-Pineda](http://xavirema.eu/)
9 | **[[Paper](https://arxiv.org/abs/2103.15145)]** **[[Project](https://team.inria.fr/robotlearn/transcenter-transformers-with-dense-queriesfor-multiple-object-tracking/)]**
10 |
11 |
12 |

13 |
14 |
15 |
16 | **MOT20 example:**
17 | 
18 |
19 |
20 | ## Bibtex
21 | **If you find this code useful, please star the project and consider citing:**
22 | ```
23 | @misc{xu2021transcenter,
24 | title={TransCenter: Transformers with Dense Representations for Multiple-Object Tracking},
25 | author={Yihong Xu and Yutong Ban and Guillaume Delorme and Chuang Gan and Daniela Rus and Xavier Alameda-Pineda},
26 | year={2021},
27 | eprint={2103.15145},
28 | archivePrefix={arXiv},
29 | primaryClass={cs.CV}
30 | }
31 | ```
32 |
33 |
34 | ## MOTChallenge Results
35 |
36 | ***For TransCenter***:
37 |
38 | MOT17 public detections:
39 |
40 | | Pretrained| MOTA | MOTP | IDF1 | FP | FN | IDS |
41 | |-----------|----------|----------|--------|-------|------|----------------|
42 | | CoCo | 71.9% | 80.5% | 64.1% | 27,356 | 126,860 | 4,118 |
43 | | CH | 75.9% | 81.2% | 65.9% | 30,190 | 100,999 | 4,626 |
44 |
45 | MOT20 public detections:
46 |
47 | | Pretrained| MOTA | MOTP | IDF1 | FP | FN | IDS |
48 | |-----------|----------|----------|--------|-------|------|----------------|
49 | | CoCo | 67.7% | 79.8% | 58.9% | 54,967 | 108,376 | 3,707 |
50 | | CH | 72.8% | 81.0% | 57.6% | 28,026 | 110,312 | 2,621 |
51 |
52 |
53 | MOT17 private detections:
54 |
55 | | Pretrained| MOTA | MOTP | IDF1 | FP | FN | IDS |
56 | |-----------|----------|----------|--------|-------|------|----------------|
57 | | CoCo | 72.7% | 80.3% | 64.0% | 33,807 | 115,542 | 4,719 |
58 | | CH | 76.2% | 81.1% | 65.5% | 40,101 | 88,827 | 5,394 |
59 |
60 | MOT20 private detections:
61 |
62 | | Pretrained| MOTA | MOTP | IDF1 | FP | FN | IDS |
63 | |-----------|----------|----------|--------|-------|------|----------------|
64 | | CoCo | 67.7% | 79.8% | 58.7% | 56,435 | 107,163 | 3,759 |
65 | | CH | 72.9% | 81.0% | 57.7% | 28,596 | 108,982 | 2,625 |
66 |
67 |
68 | **Note:**
69 | - The results can be slightly different depending on the running environment.
70 | - We might keep updating the results in the near future.
71 |
72 | ## Acknowledgement
73 |
74 | The code for TransCenterV2, TransCenter-Lite is modified and network pre-trained weights are obtained from the following repositories:
75 |
76 | 1) The PVTv2 backbone pretrained models from PVTv2.
77 | 2) The data format conversion code is modified from CenterTrack.
78 |
79 | [**CenterTrack**](https://github.com/xingyizhou/CenterTrack), [**Deformable-DETR**](https://github.com/fundamentalvision/Deformable-DETR), [**Tracktor**](https://github.com/phil-bergmann/tracking_wo_bnw).
80 | ```
81 | @article{zhou2020tracking,
82 | title={Tracking Objects as Points},
83 | author={Zhou, Xingyi and Koltun, Vladlen and Kr{\"a}henb{\"u}hl, Philipp},
84 | journal={ECCV},
85 | year={2020}
86 | }
87 |
88 | @InProceedings{tracktor_2019_ICCV,
89 | author = {Bergmann, Philipp and Meinhardt, Tim and Leal{-}Taix{\'{e}}, Laura},
90 | title = {Tracking Without Bells and Whistles},
91 | booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
92 | month = {October},
93 | year = {2019}}
94 |
95 | @article{zhu2020deformable,
96 | title={Deformable DETR: Deformable Transformers for End-to-End Object Detection},
97 | author={Zhu, Xizhou and Su, Weijie and Lu, Lewei and Li, Bin and Wang, Xiaogang and Dai, Jifeng},
98 | journal={arXiv preprint arXiv:2010.04159},
99 | year={2020}
100 | }
101 |
102 | @article{zhang2021bytetrack,
103 | title={ByteTrack: Multi-Object Tracking by Associating Every Detection Box},
104 | author={Zhang, Yifu and Sun, Peize and Jiang, Yi and Yu, Dongdong and Yuan, Zehuan and Luo, Ping and Liu, Wenyu and Wang, Xinggang},
105 | journal={arXiv preprint arXiv:2110.06864},
106 | year={2021}
107 | }
108 |
109 | @article{wang2021pvtv2,
110 | title={Pvtv2: Improved baselines with pyramid vision transformer},
111 | author={Wang, Wenhai and Xie, Enze and Li, Xiang and Fan, Deng-Ping and Song, Kaitao and Liang, Ding and Lu, Tong and Luo, Ping and Shao, Ling},
112 | journal={Computational Visual Media},
113 | volume={8},
114 | number={3},
115 | pages={1--10},
116 | year={2022},
117 | publisher={Springer}
118 | }
119 | ```
120 | Several modules are from:
121 |
122 | **MOT Metrics in Python**: [**py-motmetrics**](https://github.com/cheind/py-motmetrics)
123 |
124 | **Soft-NMS**: [**Soft-NMS**](https://github.com/DocF/Soft-NMS)
125 |
126 | **DETR**: [**DETR**](https://github.com/facebookresearch/detr)
127 |
128 | **DCNv2**: [**DCNv2**](https://github.com/CharlesShang/DCNv2)
129 |
130 | **PVTv2**: [**PVTv2**](https://github.com/whai362/PVT)
131 |
132 | **ByteTrack**: [**ByteTrack**](https://github.com/ifzhang/ByteTrack)
133 |
134 |
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