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 271–280 of 305 papers

TitleStatusHype
What can I do here? Leveraging Deep 3D saliency and geometry for fast and scalable multiple affordance detectionCode0
Unsupervised One-shot Learning of Both Specific Instances and Generalised Classes with a Hippocampal ArchitectureCode0
Learning Symbolic Task Representation from a Human-Led Demonstration: A Memory to Store, Retrieve, Consolidate, and Forget ExperiencesCode0
Learning to learn with backpropagation of Hebbian plasticityCode0
Learning to Remember Rare EventsCode0
Non-Local Representation based Mutual Affine-Transfer Network for Photorealistic StylizationCode0
Active One-shot LearningCode0
Emulating Brain-like Rapid Learning in Neuromorphic Edge ComputingCode0
The Omniglot challenge: a 3-year progress reportCode0
One Shot Learning for Deformable Medical Image Registration and Periodic Motion TrackingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified