myt889/CoMatch

Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization, ICCV 2021 (Salesforce Research).

This is a PyTorch implementation of the CoMatch paper [Blog]:

@inproceedings{CoMatch,
	title={Semi-supervised Learning with Contrastive Graph Regularization},
	author={Junnan Li and Caiming Xiong and Steven C.H. Hoi},
	booktitle={ICCV},
	year={2021}
}

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/