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Models/ProRandConv (ResNet18)

ProRandConv (ResNet18)

Reported on 3 benchmarks across 3 tasks · 1 paper · 2 SOTA

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

Computer Vision4 results

Domain GeneralizationonPACS
Accuracy· 2023-04-02
68.88
best: 70.37 (Crafting-Shifts(ResNet18))
SOTA
Progressive Random Convolutions for Single Domain Generalization arXiv:2304.00424
Single-Source Domain GeneralizationonPACS
Accuracy· 2023-04-02
68.88
best: 70.37 (Crafting-Shifts(ResNet18))
SOTA
Progressive Random Convolutions for Single Domain Generalization arXiv:2304.00424
Domain GeneralizationonPACS
Accuracy· 2023-04-02
62.89
best: 70.37 (Crafting-Shifts(ResNet18))
Progressive Random Convolutions for Single Domain Generalization arXiv:2304.00424
Single-Source Domain GeneralizationonPACS
Accuracy· 2023-04-02
62.89
best: 70.37 (Crafting-Shifts(ResNet18))
Progressive Random Convolutions for Single Domain Generalization arXiv:2304.00424

Methodology2 results

Domain AdaptationonPACS
Accuracy· 2023-04-02
68.88
best: 88.09 (SSGEN)
Progressive Random Convolutions for Single Domain Generalization arXiv:2304.00424
Domain AdaptationonPACS
Accuracy· 2023-04-02
62.89
best: 88.09 (SSGEN)
Progressive Random Convolutions for Single Domain Generalization arXiv:2304.00424