5 accepted papers
RGB-D has gradually become a crucial data source for understanding complex scenes in assisted driving. However, existing studies have paid insufficient attention to the intrinsic spatial properties of depth maps. This oversight significantly impacts the attention representation, leading to predictio
Roof wireframe reconstruction has shown great success in 3D building reconstruction due to its lightweight nature and straightforward representation. However, previous methods consider all roof points, which result in edge redundancy and omissions. In this paper, we propose a novel and streamlined E…
Building reconstruction is a challenging problem at the intersection of computer vision, photogrammetry and computer graphics. 3D wireframe presents a compelling representation for building modeling through its compact structure. Existing wireframe reconstruction methods employing vertex detection a…
Open-Vocabulary semantic segmentation (OVSS) and domain generalization in semantic segmentation (DGSS) highlight a subtle complementarity that motivates Open-Vocabulary Domain-Generalized Semantic Segmentation (OV-DGSS). OV-DGSS aims to generate pixel-level masks for unseen categories while maintain…
Vision Foundation Models (VFMs) have delivered remarkable performance in Domain Generalized Semantic Segmentation (DGSS). However, recent methods often overlook the fact that visual cues are susceptible, whereas the underlying geometry remains stable, rendering depth information more robust. In this…