ReCLIP++ rectifies class and space biases in CLIP via separate reference and positional features, logit subtraction, and a mask decoder with contrastive loss to improve unsupervised semantic segmentation on PASCAL VOC, ADE20K and other benchmarks.
C2am: contrastive learning of class- agnostic activation map for weakly supervised object localization and semantic segmentation,
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ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation
ReCLIP++ rectifies class and space biases in CLIP via separate reference and positional features, logit subtraction, and a mask decoder with contrastive loss to improve unsupervised semantic segmentation on PASCAL VOC, ADE20K and other benchmarks.