The code for CVPR2019 Oral paper "A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images"
This repository constains the codes and ShapeNet-Skeleton.zip datasets for the Paper.
This implementation uses Pytorch and TensorFlow.
For each stage, please follow the README.md under the Skeleton_inference/Volume_refinement/Mesh_refinement
folder.
python demo_im2mesh.py
python demo_deform.py
If you find this work useful in your research, please consider citing:
@InProceedings{Tang_2019_CVPR,
author = {Tang, Jiapeng and Han, Xiaoguang and Pan, Junyi and Jia, Kui and Tong, Xin},
title = {A Skeleton-Bridged Deep Learning Approach for Generating Meshes of Complex Topologies From Single RGB Images},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}
If you have any questions, please feel free to contact with Tang Jiapeng [email protected].