3 papers
cs.CV2025
Prototypical Progressive Alignment and Reweighting for Generalizable Semantic Segmentation
Yuhang Zhang, Zhengyu Zhang, Muxin Liao +4
Generalizable semantic segmentation aims to perform well on unseen target domains, a critical challenge due to real-world applications requiring high generalizability. Class-wise p…
cs.CV2025
Depth-Sensitive Soft Suppression with RGB-D Inter-Modal Stylization Flow for Domain Generalization Semantic Segmentation
Binbin Wei, Yuhang Zhang, Shishun Tian +3
Unsupervised Domain Adaptation (UDA) aims to align source and target domain distributions to close the domain gap, but still struggles with obtaining the target data. Fortunately,…
cs.CV2023
Calibration-based Dual Prototypical Contrastive Learning Approach for Domain Generalization Semantic Segmentation
Muxin Liao, Shishun Tian, Yuhang Zhang +3
Prototypical contrastive learning (PCL) has been widely used to learn class-wise domain-invariant features recently. These methods are based on the assumption that the prototypes,…