Long-Short Temporal Contrastive Learning of Video Transformers

@article{Wang2021LongShortTC,
  title={Long-Short Temporal Contrastive Learning of Video Transformers},
  author={Jue Wang and Gedas Bertasius and Du Tran and Lorenzo Torresani},
  journal={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={13990-14000}
}
Video transformers have recently emerged as a competitive alternative to 3D CNNs for video understanding. However, due to their large number of parameters and reduced inductive biases, these models require supervised pretraining on large-scale image datasets to achieve top performance. In this paper, we empirically demonstrate that self-supervised pretraining of video transformers on video-only datasets can lead to action recognition results that are on par or better than those obtained with… 

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