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Temporal Cycle-Consistency Learning
[article]
2019
arXiv
pre-print
We introduce a self-supervised representation learning method based on the task of temporal alignment between videos. The method trains a network using temporal cycle consistency (TCC), a differentiable cycle-consistency loss that can be used to find correspondences across time in multiple videos. The resulting per-frame embeddings can be used to align videos by simply matching frames using the nearest-neighbors in the learned embedding space. To evaluate the power of the embeddings, we densely
arXiv:1904.07846v1
fatcat:oytx6gdzgzbmnb527jt2csbnvi