Added 2 related papers

[bupt-ai-cz]

We have added 3 related papers, the details and keywords are as follows:

• Instance Adaptive Self-Training for Unsupervised Domain Adaptation [ECCV 2020] [Pytorch]
  • [Trasnfer Learning, Domain Adaptation, Unsupervised Domain Adaptation, Self-training, Semantic Segmentation]
• Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
  • [Domain Adaptation, Unsupervised Domain Adaptation, Adversarial Training, Trasnfer Learning, Semantic Segmentation, Medical]
• Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
  • [Trasnfer Learning, Domain Adaptation, Unsupervised Domain Adaptation, Multi-source Domain Adaptation, Dataset, Text Recognition, Self-training, Meta-learning, Benchmark]

[artix41]

Thanks for your contributions! :)

Shouldn't the dataset you've added be part of the "Image-to-image" section instead of "Other"? Also, could you replace the GitHub links with the Arxiv links? Thanks!

[bupt-ai-cz]

Thanks for your reply! We have updated paper links. "Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark" has built a dataset for Text Recognition which contains images from multi-source domain, and there is not the "Text Recognition" section so I put it into "Image-to-Image". For more details, please visit the corresponding paperswithcode.