Learning Time in Static Classifiers

Xi Ding, Lei Wang, Piotr Koniusz, Yongsheng Gao

Citation

@inproceedings{ding2026learning,
  title={Learning Time in Static Classifiers},
  author={Ding, Xi and Wang, Lei and Koniusz, Piotr and Gao, Yongsheng},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  year={2026}
}

Overview

We present a framework for learning temporal patterns in videos by modeling how visual features evolve over time. Temporally smooth video sequences are processed by a frozen image pretrained vision transformer to extract frame level features, and a lightweight temporal classifier learns feature trajectories across frames. These trajectories are optimized under the Support Exemplar Query learning framework to achieve accurate classification and maintain smooth and consistent temporal evolution.