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VideoMAE | Awesome Repository

MCG-NJUVideoMAE

0

View on GitHub↗

1,760 stars·168 forks·Python·NOASSERTION·0 viewsarxiv.org/abs/2203.12602↗

VideoMAE

Features

Perception Models - Data-efficient self-supervised pre-training for video models.
Video Understanding and Tracking - Masked autoencoders for self-supervised video pre-training.

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[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training