PRCL: Probabilistic Representation Contrastive Learning for
Semi-Supervised Semantic Segmentation
PRCL: Probabilistic Representation Contrastive Learning for
Semi-Supervised Semantic Segmentation
Tremendous breakthroughs have been developed in Semi-Supervised Semantic Segmentation (S4) through contrastive learning. However, due to limited annotations, the guidance on unlabeled images is generated by the model itself, which inevitably exists noise and disturbs the unsupervised training process. To address this issue, we propose a robust contrastive-based S4 framework, …