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Models/Finetune

Finetune

Reported on 6 benchmarks across 4 tasks · 2 papers · 2 SOTA

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

Computer Vision5 results

2D Pose EstimationonMP100
Mean PCK@0.2 - 1shot· 2019-10-01
63.58
best: 92.6 (CapeLLM)
SOTA
Revisiting Fine-tuning for Few-shot Learning arXiv:1910.00216
Image ClassificationonMeta-Dataset
Accuracy· 2019-03-07
58.758
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples arXiv:1903.03096
Image ClassificationonMeta-Dataset Rank
Mean Rank· 2019-03-07
8.7
best: 11.8 (Relation Networks)
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples arXiv:1903.03096
Few-Shot Image ClassificationonMeta-Dataset
Accuracy· 2019-03-07
58.758
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples arXiv:1903.03096
Few-Shot Image ClassificationonMeta-Dataset Rank
Mean Rank· 2019-03-07
8.7
best: 11.8 (Relation Networks)
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples arXiv:1903.03096

Methodology1 result

2D ClassificationonMP100
Mean PCK@0.2 - 1shot· 2019-10-01
63.58
best: 92.6 (CapeLLM)
SOTA
Revisiting Fine-tuning for Few-shot Learning arXiv:1910.00216