Learning Correspondence From the Cycle-Consistency of Time

CVPR 2019 Xiaolong Wang Allan Jabri Alexei A. Efros

We introduce a self-supervised method for learning visual correspondence from unlabeled video. The main idea is to use cycle-consistency in time as free supervisory signal for learning visual representations from scratch... (read more)

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