Semantic Segmentation of Textured Non-manifold 3D Meshes using Transformers

ArXi:2604.01836v1 Announce Type: new Textured 3D meshes jointly represent geometry, topology, and appearance, yet their irregular structure poses significant challenges for deep-learning-based semantic segmentation. While a few recent methods operate directly on meshes without imposing geometric constraints, they typically overlook the rich textural information also provided by such meshes. We