SUR-pnf

Reported on 4 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 Vision4 results

Image ClassificationonMeta-Dataset
Accuracy· 2020-03-20
69.3
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification arXiv:2003.09338
Image ClassificationonMeta-Dataset Rank
Mean Rank· 2020-03-20
4.25
best: 11.8 (Relation Networks)
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification arXiv:2003.09338
Few-Shot Image ClassificationonMeta-Dataset
Accuracy· 2020-03-20
69.3
best: 85.27 (SMAT (DINO-VIT-Base-16-224))
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification arXiv:2003.09338
Few-Shot Image ClassificationonMeta-Dataset Rank
Mean Rank· 2020-03-20
4.25
best: 11.8 (Relation Networks)
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification arXiv:2003.09338