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AIM: Adapting Image Models for Efficient Video Action Recognition
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Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, Mu Li
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2026-02-16 15:36:00
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AIM: Adapting Image Models for Efficient Video Action Recognition AIM: Adapting Image Models for Efficient Video Action Recognition Taojiannan Yang ♠,♣ , Yi Zhu ♠ , Yusheng Xie ♠ , Aston Zhang ♠ , Chen Chen ♣ , Mu Li ♠ ♠ Amazon Web Services, ♣ University of Central Florida Paper Code Introduction In video understanding, a common practice is bootstrapping from an image pre-trained model and then finetuning on the video data. There are two dominating directions as shown in the left part of the figure above, one is to extend an image model with additional temporal module, the other is to inflate an image model to a video model. However, full finetuning such a video model could be computationally expensive and unnecessary, given that the pre-trained image transformer models have demonstrated exceptional transferability. In this work, we propose a ...
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