OatmealLiu / MSc-iNCD

PyTorch implementation for the paper Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery

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This Github repository contains the PyTor presents the PyTorch implementation for the ICPR 2024 paper Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery [arXiv].

Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery

Accepted to International Conference on Pattern Recognition (ICPR) 2024, Kolkata, India

Mingxuan Liu, Subhankar Roy, Zhun Zhong, Nicu Sebe, and Elisa Ricci

Preparation

Training

Evaluation

License

Please check the MIT license that is listed in this repository.

Cite

If you find our framework or paper useful, please cite:

@article{liu2023large,
  title={Large-scale pre-trained models are surprisingly strong in incremental novel class discovery},
  author={Liu, Mingxuan and Roy, Subhankar and Zhong, Zhun and Sebe, Nicu and Ricci, Elisa},
  journal={arXiv preprint arXiv:2303.15975},
  year={2023}
}

The codebase for the adapted methods is created by FRoST, ResTune, Mammoth, AutoNovel, and OCRA. If you find these adapted methods useful, it would be appreciated if you acknowledge the original papers by citing them using the name and URL mentioned before.

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PyTorch implementation for the paper Large-scale Pre-trained Models are Surprisingly Strong in Incremental Novel Class Discovery

License:MIT License


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