https://github.com/salesforce/CoMatch

Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
https://github.com/salesforce/CoMatch

contrastive-learning representation-learning self-supervised-learning semi-supervised-learning

Last synced: about 1 year ago
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Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

• Host: GitHub
• URL: https://github.com/salesforce/CoMatch
• Owner: salesforce
• License: bsd-3-clause
• Created: 2021-02-25T06:24:12.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2021-10-12T19:06:44.000Z (over 4 years ago)
• Last Synced: 2025-04-15T14:53:36.746Z (about 1 year ago)
• Topics: contrastive-learning, representation-learning, self-supervised-learning, semi-supervised-learning
• Language: Python
• Homepage:
• Size: 496 KB
• Stars: 127
• Watchers: 4
• Forks: 24
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt
  • Code of conduct: CODE_OF_CONDUCT.md
  • Codeowners: CODEOWNERS
  • Security: SECURITY.md

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README

          
## 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/