Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction
This repository contains the code and data for the paper “Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction” by Takuma Yagi, Md. Tasnimul Hasan and Yoichi Sato.
Requirements
- Python 3.6+
- ffmpeg
- numpy
- opencv-python
- pillow
- scikit-learn
- python-Levenshtein
- pycocotools
- torch (1.8.1, 1.4.0- for flow generation)
- torchvision (0.9.1)
- mllogger
- flownet2-pytorch
Caution: This repository requires ~100GB space for testing, ~200GB space for trusted label training and ~3TB space for full training.
Getting Started
Download the data
- Download EPIC-KITCHENS-100 videos from the official site. Since this dataset uses 480p frames and optical flows for training and testing you need to download the original videos. Place them to