This repo is official implementation of High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition(CVPR 2023).

conda env create -f environment.yml

We use subdivided MANO to register 3D hand Mesh from "DeepHandMesh". Download joint annotation and our processed dataset from here. After downloading, put the contents in $root/data directory.

Download images for DeephandMesh and following the unzip instructions. Then, put the images folder under $root/data/DeepHandMesh directory

Download subdivided MANO from here and put the contents under $root/assets/. Download MANO from here. Put models folder under $root/assets/mano.

Download pretrained model from here and put the contents under $root/model.

python main.py --test --nmp --nrd

python main.py --nmp --nrd

@InProceedings{Luan_2023_CVPR,
    author    = {Luan, Tianyu and Zhai, Yuanhao and Meng, Jingjing and Li, Zhong and Chen, Zhang and Xu, Yi and Yuan, Junsong},
    title     = {High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2023},
    pages     = {16795-16804}
}

This repo inherited code from DeepHandMesh and S2HAND.