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cs.CV2025
DINOv3
Oriane Siméoni, Huy V. Vo, Maximilian Seitzer +23
Self-supervised learning holds the promise of eliminating the need for manual data annotation, enabling models to scale effortlessly to massive datasets and larger architectures. B…
cs.CV2025
Cluster and Predict Latent Patches for Improved Masked Image Modeling
Timothée Darcet, Federico Baldassarre, Maxime Oquab +2
Masked Image Modeling (MIM) offers a promising approach to self-supervised representation learning, however existing MIM models still lag behind the state-of-the-art. In this paper…