We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in part-aware manner. Once trained, the network can generate from scratch or predict textures given 3D mesh, without image guidance. Plausible and diverse be generated same mesh part, while texture compatibility between parts shape is achieved via conditional generation. Specifically, our method produces maps in...