CoMatch
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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/