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Rethinking Evaluation Protocols of Visual Representations Learned via Self-supervised Learning
Linear probing (LP) (and $k$-NN) on the upstream dataset with labels (e. g., ImageNet) and transfer learning (TL) to various downstream datasets are commonly employed to evaluate the quality of visual representations learned via self-supervised learning (SSL).
Weakly Supervised Segmentation of Small Buildings With Point Labels
In this paper, we present a weakly supervised segmentation network for aerial/satellite images, separately considering small and large objects.
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