HF Daily Papers
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PixCon: Clean-Positive Contrastive Learning for Foundation-Model Semi-Supervised Segmentation
Semi-supervised semantic segmentation (SSSS) has long turned on one question, which pseudo-labels to trust, and answered it with ever more careful confidence filtering. Foundation backbones change the regime: with a DINOv2 teacher a strict threshold already retains a measured 98%-clean pseudo-label