How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
More Details coming soon. If you have any questions regarding our code, please contact asharma@eng.ucsd.edu ILA-DA CVPR2021
The main features of astuti/ila-da are: General Adaptation Techniques.
Open-source alternatives to astuti/ila-da include: bit-da/tsa — [CVPR 2021 Oral] Code release for "Transferable Semantic Augmentation for Domain Adaptation". corenel/pytorch-atda — A PyTorch implementation for Asymmetric Tri-training for Unsupervised 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. bit-da/dda — Code release for "Dynamic Domain Adaptation for Efficient Inference" (CVPR 2021).
CVPR 2021 Oral Code release for "Transferable Semantic Augmentation for Domain Adaptation"
A PyTorch implementation for Asymmetric Tri-training for Unsupervised Domain Adaptation
code of Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations (CVPR2020 oral)
Code release for "Dynamic Domain Adaptation for Efficient Inference" (CVPR 2021)