idstcv / TeS

PyTorch Implementation for TeS

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TeS

PyTorch Implementation for Our ICCV'23 Paper: "Improved Visual Fine-tuning with Natural Language Supervision"

Requirements

  • Python 3.8
  • PyTorch 1.11
  • transformers 4.30.2

Usage:

TeS on CIFAR-100

  • Prepare the CIFAR100 dataset.
  • Download the checkpoint of ResNet50 pre-trained by MoCo from Link
  • Run the command below.
sh run_TeS.sh

Citation

If you use the package in your research, please cite our paper:

@article{wang2023improved,
  title={Improved Visual Fine-tuning with Natural Language Supervision},
  author={Wang, Junyang and Xu, Yuanhong and Hu, Juhua and Yan, Ming and Sang, Jitao and Qian, Qi},
  booktitle = {{IEEE} International Conference on Computer Vision, {ICCV} 2023},
  year={2023}
}

About

PyTorch Implementation for TeS

License:Apache License 2.0


Languages

Language:Python 98.1%Language:Shell 1.9%