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 221–230 of 305 papers

TitleStatusHype
Trading robust representations for sample complexity through self-supervised visual experience—0
Unsupervised Meta-Learning For Few-Shot Image Classification—0
Tackling Early Sparse Gradients in Softmax Activation Using Leaky Squared Euclidean Distance—0
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identificationCode0
Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks—0
Face Verification and Forgery Detection for Ophthalmic Surgery Images—0
Multimodal One-Shot Learning of Speech and ImagesCode0
A Deep One-Shot Network for Query-based Logo RetrievalCode0
Learning from limited datasets: Implications for Natural Language Generation and Human-Robot Interaction—0
Investigation of using disentangled and interpretable representations with language conditioning for cross-lingual voice conversion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified