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Pushing the Limits of Self-Supervised ResNets: DeepMind’s ReLICv2 Beats Strong Supervised Baselines on ImageNet
Jan. 17, 2022, 2:57 p.m. | Synced
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A DeepMind research team proposes ReLICv2, which demonstrates for the first time that representations learned without labels can consistently outperform a strong, supervised baseline on ImageNet and even achieve comparable results to state-of-the-art self-supervised vision transformers (ViTs).
The post Pushing the Limits of Self-Supervised ResNets: DeepMind’s ReLICv2 Beats Strong Supervised Baselines on ImageNet first appeared on Synced.
ai artificial intelligence computer vision & graphics deepmind imagenet machine learning machine learning & data science ml research resnet-50 self-supervised learning technology
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