GSF&PPF

Code release for ``Towards Discovering the Effectiveness of Moderately Confident Samples for Semi-Supervised Learning'' published in CVPR 2022.

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Requirements

• python 3.6.4
• pytorch 1.4.0
• torchvision 0.5.0

Data preparation

The references of the used datasets are included in the paper.

Model training

1. Install necessary python packages.
2. Replace root and dataset in run.sh with those in one's own system.
3. Run command sh run.sh.

The results are saved in the folder ./results/.

Paper citation

@InProceedings{tang2022towards,
    author    = {Tang, Hui and Jia, Kui},
    title     = {Towards Discovering the Effectiveness of Moderately Confident Samples for Semi-Supervised Learning},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2022},
    pages     = {14658-14667}
}