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SotA/Computer Vision/Image Classification/Mini-ImageNet-CUB 5-way (1-shot)

Image Classification on Mini-ImageNet-CUB 5-way (1-shot)

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼Extra DataPaperDate↕Code
1TRIDENT84.61NoTransductive Decoupled Variational Inference for...2022-08-22Code
2PEMnE-BMS*63.9NoSqueezing Backbone Feature Distributions to the ...2021-10-18Code
3PT+MAP62.49NoLeveraging the Feature Distribution in Transfer-...2020-06-06Code
4DAPNA49.44NoFew-Shot Learning as Domain Adaptation: Algorith...2020-02-06-
5MatchingNet (Vinyals et al., 2016)45.59NoMatching Networks for One Shot Learning2016-06-13Code
6ProtoNet (Snell et al., 2017)45.31NoPrototypical Networks for Few-shot Learning2017-03-15Code
7RelationNet (Sung et al., 2018)42.91NoLearning to Compare: Relation Network for Few-Sh...2017-11-16Code
8DKT + CosSim40.22NoBayesian Meta-Learning for the Few-Shot Setting ...2019-10-11Code
9MAML (Finn et al., 2017)40.15NoModel-Agnostic Meta-Learning for Fast Adaptation...2017-03-09Code
10HyperShot40.03NoHyperShot: Few-Shot Learning by Kernel HyperNetw...2022-03-21Code
11FEAT (Ye et al., 2018)39NoFew-Shot Learning via Embedding Adaptation with ...2018-12-10Code
12Baseline++ (Chen et al., 2019)33.04NoA Closer Look at Few-shot Classification2019-04-08Code