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SOTA
少样本图像分类
Few Shot Image Classification On Mini 5
Few Shot Image Classification On Mini 5
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Accuracy
Paper Title
Repository
TRIDENT
84.61
Transductive Decoupled Variational Inference for Few-Shot Classification
PEMnE-BMS*
63.90
Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning
PT+MAP
62.49
Leveraging the Feature Distribution in Transfer-based Few-Shot Learning
DAPNA
49.44
Few-Shot Learning as Domain Adaptation: Algorithm and Analysis
-
MatchingNet (Vinyals et al., 2016)
45.59
Matching Networks for One Shot Learning
ProtoNet (Snell et al., 2017)
45.31
Prototypical Networks for Few-shot Learning
RelationNet (Sung et al., 2018)
42.91
Learning to Compare: Relation Network for 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
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
Baseline++ (Chen et al., 2019)
33.04
A Closer Look at Few-shot Classification
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Few Shot Image Classification On Mini 5 | SOTA | HyperAI超神经