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Code for CAiDA
The main features of learning-group123/caida are: Multi-Source Adaptation, Source Free Domain Adaptation.
Projects with overlapping indexed features include: altschulerwu-lab/mulann — Code and data of the "Multi-domain adversarial learning" paper, Schoenauer-Sebag et al., accepted at ICLR 2019. bupt-ai-cz/meta-selflearning — Meta Self-learning for Multi-Source Domain Adaptation： A Benchmark. chrisallenming/ltc-msda — Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020). daoyuan98/mdda — Implementation of paper multi-source distilling domain adaptation. davidpengucf/rain — python == 3.6.8 - pytorch ==1.1.0 - torchvision == 0.3.0 - numpy, scipy, sklearn, PIL, argparse, tqdm. albert0147/g-sfda — code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'.
Code and data of the "Multi-domain adversarial learning" paper, Schoenauer-Sebag et al., accepted at ICLR 2019
Meta Self-learning for Multi-Source Domain Adaptation： A Benchmark
Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020).
code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'