ALTrack is a coherent point tracking framework which designes an autogenic language embedding for visual feature enhancement, strengthens point correspondence in long-term sequences. Unlike existing visual-language schemes, our approach learns text embeddings from visual features through a dedicated mapping network, enabling seamless adaptation to various tracking tasks without explicit text annotations. Additionally, we introduce a consistency decoder that efficiently integrates text tokens into visual features with minimal computational overhead.

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@inproceedings{song2024altrack,
  title={Autogenic Language Embedding for Coherent Point Tracking},
  author={Song, Zikai and Tang, Ying and Luo, Run and Ma, Lintao and Yu, Junqing and Chen, Yi-Ping Phoebe and Yang, Wei},
  booktitle={Proceedings of the 29th ACM International Conference on Multimedia},
  year={2024}
}