Md. Al-Masrur Khan

AFRDA: Attentive Feature Refinement for Domain Adaptive Semantic Segmentation

In Unsupervised Domain Adaptive Semantic Segmentation (UDA-SS), a model is trained on labeled source domain data (e.g., synthetic images) and adapted to an unlabeled target domain (e.g., real-world images) without access to target annotations. Existing UDA-SS methods often struggle to balance fine-g