SOTAVerified

One-Shot Learning

One-shot learning is the task of learning information about object categories from a single training example.

( Image credit: Siamese Neural Networks for One-shot Image Recognition )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 305 papers

TitleStatusHype
One-Shot Instance SegmentationCode1
Dynamic Few-Shot Visual Learning without ForgettingCode1
One-Shot Learning for Semantic SegmentationCode1
Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksCode1
Matching Networks for One Shot LearningCode1
Adaptive Noise Resilient Keyword Spotting Using One-Shot Learning—0
Interactive Instance Annotation with Siamese Networks—0
Federated One-Shot Learning with Data Privacy and Objective-Hiding—0
Transductive One-Shot Learning Meet Subspace Decomposition—0
PVChat: Personalized Video Chat with One-Shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified