CycleCL: Self-supervised Learning for Periodic Videos

no code implementations • 5 Nov 2023 • Matteo Destro, Michael Gygli

We start from the insight that a good visual representation for periodic data should be sensitive to the phase of a cycle, but be invariant to the exact repetition, i. e. it should generate identical representations for a specific phase throughout all repetitions.

Contrastive Learning Self-Supervised Learning