June 17, 2022, 1:11 a.m. | Fatemeh Saleh, Fuwen Tan, Adrian Bulat, Georgios Tzimiropoulos, Brais Martinez

cs.LG updates on arXiv.org arxiv.org

Learning visual representations through self-supervision is an extremely
challenging task as the network needs to sieve relevant patterns from spurious
distractors without the active guidance provided by supervision. This is
achieved through heavy data augmentation, large-scale datasets and prohibitive
amounts of compute. Video self-supervised learning (SSL) suffers from added
challenges: video datasets are typically not as large as image datasets,
compute is an order of magnitude larger, and the amount of spurious patterns
the optimizer has to sieve through is …

arxiv cv image learning representation representation learning video

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