AI RESEARCH
Recurrent Video Masked Autoencoders
arXiv CS.CV
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ArXi:2512.13684v2 Announce Type: replace We present Recurrent Video Masked-Autoencoders (RVM): a novel approach to video representation learning that leverages recurrent computation to model the temporal structure of video data. RVM couples an asymmetric masking objective with a transformer-based recurrent neural network to aggregate information over time