NAIMA: Semantics Aware RGB Guided Depth Super-Resolution
The paper 'NAIMA: Semantics Aware RGB Guided Depth Super-Resolution' addresses limitations in traditional depth super-resolution where color cues do not align with true geometric edges. The authors propose a method using semantic guidance and a Guided Token Alignment (GTA) module to intelligently integrate low-resolution depth structure with high-resolution RGB features, resulting in more reliable and geometrically accurate data for applications like autonomous robotics.