git clone https://github.com/val-iisc/s3vaada.git
cd s3vaada/
pip install -r requirements.txt
cd models/
wget https://download.pytorch.org/models/resnet50-19c8e357.pth
mv resnet50-19c8e357.pth resnet50.pth
cd ../

cd datasets/
sh get_office.sh
python preprocess_office31.py
cd ../

cd datasets/
sh get_office-home.sh
python preprocess_office-home.py
cd ../

python main.py --name w2a-s3vaada --source webcam --target amazon

@InProceedings{Rangwani_2021_ICCV,
    author    = {Rangwani, Harsh and Jain, Arihant and Aithal, Sumukh K and Babu, R. Venkatesh},
    title     = {S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {7516-7525}
}