Summary of Sutrack: Towards Simple and Unified Single Object Tracking, by Xin Chen and Ben Kang and Wanting Geng and Jiawen Zhu and Yi Liu and Dong Wang and Huchuan Lu
SUTrack: Towards Simple and Unified Single Object Tracking
by Xin Chen, Ben Kang, Wanting Geng, Jiawen Zhu, Yi Liu, Dong Wang, Huchuan Lu
First submitted to arxiv on: 26 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a unified single object tracking (SOT) framework, SUTrack, which can handle five different SOT tasks with a single model trained in one session. Unlike current methods that design individual architectures for each task and train separate models, SUTrack demonstrates that a unified input representation can effectively handle various common SOT tasks without the need for task-specific designs or separate training sessions. The framework also introduces a task-recognition auxiliary training strategy and soft token type embedding to enhance its performance with minimal overhead. Experiments show that SUTrack outperforms previous task-specific counterparts across 11 datasets, and it provides models catering to edge devices and high-performance GPUs, striking a good trade-off between speed and accuracy. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a single object tracking system that can do five different tasks at once. Right now, people have to design special systems for each task and train them separately. This new system shows that you can use one model for all these tasks without having to design something new for each one. It also has some extra tricks to make it work better with less effort. The tests showed that this system is better than the ones that were designed specifically for each task, and it’s fast enough to run on both simple devices and powerful computers. |
Keywords
» Artificial intelligence » Embedding » Object tracking » Token
