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 281–290 of 305 papers

TitleStatusHype
Active One-shot LearningCode0
Discovering objects and their relations from entangled scene representations—0
Fast Adaptation in Generative Models with Generative Matching Networks—0
Inverting The Generator Of A Generative Adversarial Network—0
Low Data Drug Discovery with One-shot Learning—0
Latent Attention For If-Then Program Synthesis—0
ARTiS: Appearance-based Action Recognition in Task Space for Real-Time Human-Robot Collaboration—0
Task Specific Adversarial Cost Function—0
Learning to learn with backpropagation of Hebbian plasticityCode0
Towards Generalizable Sentence Embeddings—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified