Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking

El-Nouby Alaaeldin
El-Nouby Alaaeldin
Susskind Joshua M.
Susskind Joshua M.
Cited by: 0|Views12

Abstract:

Deep neural networks require collecting and annotating large amounts of data to train successfully. In order to alleviate the annotation bottleneck, we propose a novel self-supervised representation learning approach for spatiotemporal features extracted from videos. We introduce Skip-Clip, a method that utilizes temporal coherence in v...More

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