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Models/MetaOptNet-SVM+Task Aug

MetaOptNet-SVM+Task Aug

Reported on 12 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 Vision12 results

Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2020-02-08
76.75
best: 89.94 (PT+MAP+SF+SOT (transductive))
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2020-02-08
82.13
best: 98.72 (SgVA-CLIP)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2020-02-08
65.38
best: 97.95 (SgVA-CLIP)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Image ClassificationonFC100 5-way (5-shot)
Accuracy· 2020-02-08
67.17
best: 70.6 (BAVARDAGE)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Image ClassificationonFC100 5-way (1-shot)
Accuracy· 2020-02-08
49.77
best: 57.27 (BAVARDAGE)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2020-02-08
88.38
best: 93.5 (CAML [Laion-2b])
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Few-Shot Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2020-02-08
76.75
best: 89.94 (PT+MAP+SF+SOT (transductive))
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2020-02-08
82.13
best: 98.72 (SgVA-CLIP)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2020-02-08
65.38
best: 97.95 (SgVA-CLIP)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Few-Shot Image ClassificationonFC100 5-way (5-shot)
Accuracy· 2020-02-08
67.17
best: 70.6 (BAVARDAGE)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Few-Shot Image ClassificationonFC100 5-way (1-shot)
Accuracy· 2020-02-08
49.77
best: 57.27 (BAVARDAGE)
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804
Few-Shot Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2020-02-08
88.38
best: 93.5 (CAML [Laion-2b])
Task Augmentation by Rotating for Meta-Learning arXiv:2003.00804