S²Contact: Graph-based Network for 3D Hand-Object Contact Estimation with Semi-Supervised Learning

This repo contains details for our paper: "S²Contact: Graph-based Network for 3D Hand-Object Contact Estimation with Semi-Supervised Learning" (ECCV 2022)

[Project Page]

Installation

This document contains detailed instructions for installing the necessary dependencied for S²Contact.

• Create and activate a conda environment

  conda create -n s2contact python=3.8
  conda activate s2contact

• Install PyTorch and PyTorch3D

  conda install -c pytorch pytorch=1.7.1 torchvision cudatoolkit=10.2
  conda install -c fvcore -c iopath -c conda-forge fvcore iopath
  conda install pytorch3d -c pytorch3d

• Install PyTorch-Geometric Please following this installation instructions

• Install Other dependencies

  pip install git+https://github.com/hassony2/manopth.git open3d tensorboardX pyquaternion trimesh transforms3d chumpy opencv-python

• Download MANO Model Download the MANO model files (mano_v1_2.zip) from MANO website.

  mano/webuser/lbs.py
  mano/models/MANO_RIGHT.pkl

Quick Start

• Quick Demo

  python network/run_contactopt.py --split=demo --model=dgcnn
  python network/run_eval.py --split=demo --model=dgcnn
  python network/run_eval.py --split=demo --model=dgcnn --vis

TODO

• To release pseudo labeled dataset.
• Upload paper to arXiv.

Acknowledgement

This repo is built upon ContactOpt. We would like to thank their authors for providing great frameworks and toolkits.

Contact

• Zhongqun Zhang (email: zxz064@student.bham.ac.uk)

• Tze Ho Elden Tse (email: txt994@student.bham.ac.uk)

  Feel free to contact me if you have additional questions.