6 citations · 14 across the 7 of their papers we have counts for
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cs.CV2021★ 1 cited
Learning to Align Sequential Actions in the Wild
Weizhe Liu, Bugra Tekin, Huseyin Coskun +3
State-of-the-art methods for self-supervised sequential action alignment rely on deep networks that find correspondences across videos in time. They either learn frame-to-frame map…
cs.CV2021
Learning by Aligning Videos in Time
Sanjay Haresh, Sateesh Kumar, Huseyin Coskun +4
We present a self-supervised approach for learning video representations using temporal video alignment as a pretext task, while exploiting both frame-level and video-level informa…