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[ICCV 2021] PyTorch implementation of "Universal Cross-Domain Retrieval: Generalizing across Classes and Domains"

License: MIT License

Shell 7.91% Python 92.09%
image-retrieval zero-shot-retrieval domain-generalization

ucdr's Introduction

UCDR

Universal Cross-Domain Retrieval: Generalizing across Classes and Domains | ICCV 2021

Requirements and Setup

Python - 3.7.6, PyTorch - 1.1.0, CUDA - 9.0, cuDNN - 7.5.1, NVIDIA Driver Version >= 384.13

conda create --name torch11 --file requirements.txt
conda activate torch11
conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=9.0 -c pytorch

Download datasets

Check downloads folder for scripts. Change path_dataset in download_sketchy.sh.

Pretrained Models

Download from here.

Reproducing our Results

Check reproduce_runs.sh per folder in src/algos.

TODOs

  • Add trainer and test files for SAKE, Doodle2Search, Base NW, EISNet, CuMix

๐ŸŽ“ Cite

If this code was helpful for your research, consider citing:

@article{paul2021universal,
  title={Universal Cross-Domain Retrieval: Generalizing Across Classes and Domains},
  author={Paul, Soumava and Dutta, Titir and Biswas, Soma},
  journal={arXiv preprint arXiv:2108.08356},
  year={2021}
}

๐Ÿ™ Acknowledgements

Parts of our code have been borrowed from the following repositories:

ucdr's People

Contributors

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Watchers

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Forkers

keshava dannielge

ucdr's Issues

About args.trainvalid

Thank you for your excellent work.
I notice that args.trainvalid exists in the domainnet.py, sketchy_extended.py and other datasets' script, but this argument does't exist in options_xxx.py.
Should I remove this argument, or set it True?

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