CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research)
This is a PyTorch implementation of the CoMatch paper [Blog]:
@article{CoMatch,
title={Semi-supervised Learning with Contrastive Graph Regularization},
author={Junnan Li and Caiming Xiong and Steven C.H. Hoi},
journal={arXiv preprint arXiv:2011.11183},
year={2020}
}
Requirements:
- PyTorch ≥ 1.4
- pip install tensorboard_logger
- download and extract cifar-10 dataset into ./data/
To perform semi-supervised learning on CIFAR-10 with 4 labels per class, run:
python Train_CoMatch.py --n-labeled 40 --seed 1
The results using different random seeds are:
| seed | 1 | 2 | 3 | 4 | 5 | avg |
|---|---|---|---|---|---|---|
| accuracy | 93.71 | 94.10 | 92.93 | 90.73 | 93.97 | 93.09 |
ImageNet
For ImageNet experiments, see ./imagenet/
