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Models/DFA-ENT

DFA-ENT

Reported on 6 benchmarks across 2 tasks · 1 paper · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology6 results

Transfer LearningonOffice-Home
Accuracy· 2020-06-23
69.2
best: 84.2 (APCLIP)
SOTA
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment arXiv:2006.12770
Domain AdaptationonUSPS-to-MNIST
Accuracy· 2020-06-23
96.2
best: 98.75 (FAMCD)
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment arXiv:2006.12770
Domain AdaptationonSVHN-to-MNIST
Accuracy· 2020-06-23
98.2
best: 99.18 (Mean teacher)
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment arXiv:2006.12770
Domain AdaptationonSYNSIG-to-GTSRB
Accuracy· 2020-06-23
96.8
best: 97.5 (DFA-MCD)
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment arXiv:2006.12770
Domain AdaptationonMNIST-to-USPS
Accuracy· 2020-06-23
97.9
best: 98.8 (FACT)
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment arXiv:2006.12770
Domain AdaptationonImageCLEF-DA
Accuracy· 2020-06-23
89.1
best: 94.3 (CMKD)
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment arXiv:2006.12770