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Models/OSLO

OSLO

Reported on 8 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.

Computer Vision8 results

Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2023-01-20
83.4
best: 98.72 (SgVA-CLIP)
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2023-01-20
71.73
best: 97.95 (SgVA-CLIP)
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390
Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2023-01-20
76.64
best: 96.8 (CAML [Laion-2b])
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390
Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2023-01-20
86.35
best: 98.8 (CAML [Laion-2b])
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2023-01-20
83.4
best: 98.72 (SgVA-CLIP)
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2023-01-20
71.73
best: 97.95 (SgVA-CLIP)
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390
Few-Shot Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· 2023-01-20
76.64
best: 96.8 (CAML [Laion-2b])
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390
Few-Shot Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· 2023-01-20
86.35
best: 98.8 (CAML [Laion-2b])
Open-Set Likelihood Maximization for Few-Shot Learning arXiv:2301.08390