Cross-Atlas Convolution for Parameterization Invariant Learning on Textured Mesh Surface

CVPR 2019 Shiwei Li Zixin Luo Mingmin Zhen Yao Yao Tianwei Shen Tian Fang Long Quan

We present a convolutional network architecture for direct feature learning on mesh surfaces through their atlases of texture maps. The texture map encodes the parameterization from 3D to 2D domain, rendering not only RGB values but also rasterized geometric features if necessary... (read more)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.