README.md

Concurrent Subsidiary Supervision for Source-Free DA (ECCV22)

Code for our ECCV 2022 paper 'Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation'.

[Paper] [Project Page]

Dataset preparation

Download the Office-Home (use our provided image list files) dataset. Put the dataset in data folder

Office-Home experiments

Code for Single Source Domain Adaptation (SSDA) is in the 'SSDA_OH' folder.

sh SSDA_OH/run.sh

Code for Multi Source Domain Adaptation (SSDA) is in the 'MSDA_OH' folder.

sh MSDA_OH/run.sh

Pre-trained checkpoints (coming soon)

Citation

If you find our work useful in your research, please cite the following paper:

@InProceedings{kundu2022concurrent,
  title={Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation},
  author={Kundu, Jogendra Nath and Bhambri, Suvaansh and Kulkarni, Akshay and Sarkar, Hiran and Jampani, Varun and Babu, R. Venkatesh},
  booktitle={European Conference on Computer Vision},
  year={2022},
}