Tackling Ambiguity in Weakly Supervised Semantic Segmentation through Uncertainty Inference and Affinity Diversification

The core message of this work is to efficiently tackle the ambiguity-induced false activation issue in both the class activation map generation and pseudo label refinement stages of weakly supervised semantic segmentation through uncertainty inference and affinity diversification.