[ { "Accuracy": 98.6, "code_links": [ { "title": "JingWang18/Discriminative-Feature-Alignment", "url": "https://github.com/JingWang18/Discriminative-Feature-Alignment" } ], "date": "2020-06-23", "date2": 20200623, "model": "DFA-MCD", "paper": { "title": "Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment", "url": "https://cknow.io/lib/6382a0bf15c7bcb0" }, "paper_data_uoa": "6382a0bf15c7bcb0" }, { "Accuracy": 98, "code_links": [ { "title": "tim-learn/SHOT", "url": "https://github.com/tim-learn/SHOT" } ], "date": "2020-02-20", "date2": 20200220, "model": "SHOT", "paper": { "title": "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation", "url": "https://cknow.io/lib/807e4845a1b634aa" }, "paper_data_uoa": "807e4845a1b634aa" }, { "Accuracy": 97.9, "code_links": [ { "title": "JingWang18/Discriminative-Feature-Alignment", "url": "https://github.com/JingWang18/Discriminative-Feature-Alignment" } ], "date": "2020-06-23", "date2": 20200623, "model": "DFA-ENT", "paper": { "title": "Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment", "url": "https://cknow.io/lib/6382a0bf15c7bcb0" }, "paper_data_uoa": "6382a0bf15c7bcb0" }, { "Accuracy": 93.8, "code_links": [ { "title": "mil-tokyo/MCD_DA", "url": "https://github.com/mil-tokyo/MCD_DA" }, { "title": "onedayatatime0923/Cycle_Mcd_Gan", "url": "https://github.com/onedayatatime0923/Cycle_Mcd_Gan" }, { "title": "HiGal/Domain-Adaptation", "url": "https://github.com/HiGal/Domain-Adaptation" }, { "title": "Nyn-ynu/MCD", "url": "https://github.com/Nyn-ynu/MCD" }, { "title": "binhuixie/summer_work", "url": "https://github.com/binhuixie/summer_work" } ], "date": "2017-12-07", "date2": 20171207, "model": "MCD", "paper": { "title": "Maximum Classifier Discrepancy for Unsupervised Domain Adaptation", "url": "https://cknow.io/lib/fd925d02efc15b5b" }, "paper_data_uoa": "fd925d02efc15b5b" }, { "Accuracy": 90.1, "code_links": [ { "title": "jvanvugt/pytorch-domain-adaptation", "url": "https://github.com/jvanvugt/pytorch-domain-adaptation" }, { "title": "erictzeng/adda", "url": "https://github.com/erictzeng/adda" }, { "title": "Carl0520/ADDA-pytorch", "url": "https://github.com/Carl0520/ADDA-pytorch" }, { "title": "anglihust/Unsupervised-vessel-segmentation", "url": "https://github.com/anglihust/Unsupervised-vessel-segmentation" }, { "title": "Fujiki-Nakamura/ADDA.PyTorch", "url": "https://github.com/Fujiki-Nakamura/ADDA.PyTorch" }, { "title": "kevin851066/Deep_Learning_for_Computer_Vision", "url": "https://github.com/kevin851066/Deep_Learning_for_Computer_Vision" }, { "title": "Jeff860530/ADDA", "url": "https://github.com/Jeff860530/ADDA" }, { "title": "v1viswan/Domain_adaptation_in_HRNet", "url": "https://github.com/v1viswan/Domain_adaptation_in_HRNet" }, { "title": "caoquanjie/ADDA-master", "url": "https://github.com/caoquanjie/ADDA-master" } ], "date": "2017-02-17", "date2": 20170217, "model": "ADDN", "paper": { "title": "Adversarial Discriminative Domain Adaptation", "url": "https://cknow.io/lib/6e78e6f933a7bf51" }, "paper_data_uoa": "6e78e6f933a7bf51" } ]