D2SL: Decouple Defogging and Semantic Learning for Foggy Domain-Adaptive Segmentation

arXiv:2404.04807v1 Announce Type: new
Abstract: We investigated domain adaptive semantic segmentation in foggy weather scenarios, which aims to enhance the utilization of unlabeled foggy data and improve the model's adaptability to foggy conditions. Current methods rely on clear images as references, jointly learning defogging and segmentation for foggy images. Despite making some progress, there are still two main drawbacks: (1) the coupling of segmentation and defogging feature representations, resulting in a decrease in semantic representation capability, and (2) the failure …

abstract adaptability arxiv clear cs.cv cs.mm current data domain images segmentation semantic type weather