Web: http://arxiv.org/abs/2206.08347

June 17, 2022, 1:13 a.m. | Matthew Gwilliam, Abhinav Shrivastava

cs.CV updates on arXiv.org arxiv.org

By leveraging contrastive learning, clustering, and other pretext tasks,
unsupervised methods for learning image representations have reached impressive
results on standard benchmarks. The result has been a crowded field - many
methods with substantially different implementations yield results that seem
nearly identical on popular benchmarks, such as linear evaluation on ImageNet.
However, a single result does not tell the whole story. In this paper, we
compare methods using performance-based benchmarks such as linear evaluation,
nearest neighbor classification, and clustering for …

analysis arxiv benchmarking cv image learning representation representation learning unsupervised

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