AI RESEARCH
Geometry Reinforced Efficient Attention Tuning Equipped with Normals for Robust Stereo Matching
arXiv CS.CV
•
ArXi:2604.09142v1 Announce Type: new Despite remarkable advances in image-driven stereo matching over the past decade, Synthetic-to-Realistic Zero-Shot (Syn-to-Real) generalization remains an open challenge. This suboptimal generalization performance mainly stems from cross-domain shifts and ill-posed ambiguities inherent in image textures, particularly in occluded, textureless, repetitive, and non-Lambertian (specular/transparent) regions.