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Few Shot Image Classification On Mini 5

Métriques

Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	Paper Title	Repository
MatchingNet (Vinyals et al., 2016)	45.59	Matching Networks for One Shot Learning
PT+MAP	62.49	Leveraging the Feature Distribution in Transfer-based Few-Shot Learning
DKT + CosSim	40.22	Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels
MAML (Finn et al., 2017)	40.15	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Baseline++ (Chen et al., 2019)	33.04	A Closer Look at Few-shot Classification
PEMnE-BMS*	63.90	Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning
HyperShot	40.03	HyperShot: Few-Shot Learning by Kernel HyperNetworks
FEAT (Ye et al., 2018)	39.00	Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions
DAPNA	49.44	Few-Shot Learning as Domain Adaptation: Algorithm and Analysis	-
TRIDENT	84.61	Transductive Decoupled Variational Inference for Few-Shot Classification
RelationNet (Sung et al., 2018)	42.91	Learning to Compare: Relation Network for Few-Shot Learning
ProtoNet (Snell et al., 2017)	45.31	Prototypical Networks for Few-shot Learning

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