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Models/VL2V-SD (CLIP, ViT-B/16)

VL2V-SD (CLIP, ViT-B/16)

Reported on 10 benchmarks across 2 tasks · 1 paper

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

Methodology5 results

Domain AdaptationonPACS
Average Accuracy· 2023-10-12
96.68
best: 99 (SIMPLE+)
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain AdaptationonOffice-Home
Average Accuracy· 2023-10-12
87.38
best: 90.6 (MoA (OpenCLIP, ViT-B/16))
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain AdaptationonDomainNet
Average Accuracy· 2023-10-12
62.79
best: 67.4 (L2C (CLIP, ViT-L/14))
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain AdaptationonVLCS
Average Accuracy· 2023-10-12
83.25
best: 85.5 (CAR-FT (CLIP, ViT-B/16))
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain AdaptationonTerraIncognita
Average Accuracy· 2023-10-12
58.54
best: 69.6 (UniDG + CORAL + ConvNeXt-B)
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255

Computer Vision5 results

Domain GeneralizationonPACS
Average Accuracy· 2023-10-12
96.68
best: 99 (SIMPLE+)
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain GeneralizationonOffice-Home
Average Accuracy· 2023-10-12
87.38
best: 90.6 (MoA (OpenCLIP, ViT-B/16))
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain GeneralizationonDomainNet
Average Accuracy· 2023-10-12
62.79
best: 67.4 (L2C (CLIP, ViT-L/14))
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain GeneralizationonVLCS
Average Accuracy· 2023-10-12
83.25
best: 85.5 (CAR-FT (CLIP, ViT-B/16))
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255
Domain GeneralizationonTerraIncognita
Average Accuracy· 2023-10-12
58.54
best: 69.6 (UniDG + CORAL + ConvNeXt-B)
Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification arXiv:2310.08255