Dino is a self-supervised learning approach for computer vision tasks. It leverages vision transformers without using any labeled data. Dino v2 introduces several improvements over its predecessor, enhancing performance and scalability. It achieves state-of-the-art results on various benchmarks. Notably, Dino v2 demonstrates strong performance on downstream tasks such as image classification and object detection.
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Paper link - https://arxiv.org/abs/2304.07193
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