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7 | 7 | <!-- TOC --> |
8 | 8 | - [综述论文](#综述论文) |
9 | 9 | - [算法论文](#算法论文) |
| 10 | + - [**2023**](#2023) |
10 | 11 | - [**2022**](#2022) |
11 | 12 | - [**2021**](#2021) |
12 | 13 | - [**2020**](#2020) |
@@ -64,6 +65,12 @@ Multiple Object Tracking in Deep Learning Approaches:A Survey [[paper](https://w |
64 | 65 | <a id="markdown-算法论文" name="算法论文"></a> |
65 | 66 | ## 算法论文 |
66 | 67 |
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| 68 | +<a id="markdown-2023" name="2023"></a> |
| 69 | +### **2023** |
| 70 | + |
| 71 | +**C-BIoU**: Hard to Track Objects with Irregular Motions and Similar Appearances? Make It Easier by Buffering the Matching Space (2nd-place solutions in the CVPR’22 SoccerNet MOT and ECCV’22 |
| 72 | +MOTComplex DanceTrack challenges)[[paper](https://arxiv.org/pdf/2211.14317.pdf)] **WACV 2023** |
| 73 | + |
67 | 74 | <a id="markdown-2022" name="2022"></a> |
68 | 75 | ### **2022** |
69 | 76 |
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@@ -143,6 +150,8 @@ Simple Cues Lead to a Strong Multi-Object Tracker [[code]()] [[paper](https://ar |
143 | 150 | <a id="markdown-2020" name="2020"></a> |
144 | 151 | ### **2020** |
145 | 152 |
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| 153 | +**ReMOTS**: ReMOTS: Self-Supervised Refining Multi-Object Tracking and Segmentation (1st-place solution for CVPR 2020 MOTS Challenge)[[paper](https://arxiv.org/pdf/2007.03200.pdf)] |
| 154 | + |
146 | 155 | **TransTrack**: TransTrack: Multiple-Object Tracking with Transformer [[code](https://github.com/PeizeSun/TransTrack)] [[paper](https://arxiv.org/pdf/2012.15460.pdf)] |
147 | 156 |
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148 | 157 | **TPAGT**: Tracklets Predicting Based Adaptive Graph Tracking [[paper](https://arxiv.org/pdf/2010.09015v3.pdf)] **original FGAGT** |
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