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 251–260 of 305 papers

TitleStatusHype
Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning—0
Exploring the potential of prototype-based soft-labels data distillation for imbalanced data classification—0
Face Verification and Forgery Detection for Ophthalmic Surgery Images—0
Fast Adaptation in Generative Models with Generative Matching Networks—0
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching—0
Federated One-Shot Learning with Data Privacy and Objective-Hiding—0
FIGO: Enhanced Fingerprint Identification Approach Using GAN and One Shot Learning Techniques—0
Generative Adversarial Residual Pairwise Networks for One Shot Learning—0
Generative One-Shot Face Recognition—0
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified