A PyTorch implementation for Asymmetric Tri-training for Unsupervised Domain Adaptation
The main features of corenel/pytorch-atda are: General Adaptation Techniques.
Open-source alternatives to corenel/pytorch-atda include: bit-da/dda — Code release for "Dynamic Domain Adaptation for Efficient Inference" (CVPR 2021). bit-da/tsa — [CVPR 2021 Oral] Code release for "Transferable Semantic Augmentation for Domain Adaptation". cuishuhao/bnm — code of Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations… enesdoruk/transadapter — TransAdapter: Vision Transformer for Feature-Centric Unsupervised Domain Adaptation. gt-ripl/l2c — Learning to Cluster. A deep clustering strategy. astuti/ila-da — More Details coming soon. If you have any questions regarding our code, please contact asharma@eng.ucsd.edu ILA-DA…
Code release for "Dynamic Domain Adaptation for Efficient Inference" (CVPR 2021)
CVPR 2021 Oral Code release for "Transferable Semantic Augmentation for Domain Adaptation"
code of Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations (CVPR2020 oral)
More Details coming soon. If you have any questions regarding our code, please contact asharma@eng.ucsd.edu ILA-DA CVPR2021