Temporal Cycle-Consistency Learning

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... (read more)

PDF Abstract CVPR 2019 PDF CVPR 2019 Abstract

Datasets


Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Video Alignment UPenn Action TCC + SaL Kendall's Tau 0.7286 # 5
Kendall's Tau 0.7328 # 4
Video Alignment UPenn Action TCC + TCN Kendall's Tau 0.7672 # 1

Methods used in the Paper


METHOD TYPE
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