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- W4292829079 abstract "We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos. Differently from previous contrast learning based methods that mostly focus on learning visual semantics (e.g., CVRL), SCVRL is capable of learning both semantic and motion patterns. For that, we reformulate the popular shuffling pretext task within a modern contrastive learning paradigm. We show that our transformer-based network has a natural capacity to learn motion in self-supervised settings and achieves strong performance, outperforming CVRL on four benchmarks." @default.
- W4292829079 created "2022-08-24" @default.
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- W4292829079 date "2022-06-01" @default.
- W4292829079 modified "2023-10-05" @default.
- W4292829079 title "SCVRL: Shuffled Contrastive Video Representation Learning" @default.
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- W4292829079 doi "https://doi.org/10.1109/cvprw56347.2022.00458" @default.
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