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 161–170 of 305 papers

TitleStatusHype
RePD: Defending Jailbreak Attack through a Retrieval-based Prompt Decomposition Process—0
Representing Signs as Signs: One-Shot ISLR to Facilitate Functional Sign Language Technologies—0
Resource Constrained Dialog Policy Learning via Differentiable Inductive Logic Programming—0
Response Matching for generating materials and molecules—0
Robust One Shot Audio to Video Generation—0
Rotation Invariance Neural Network—0
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition—0
Similarity Learning Networks for Animal Individual Re-Identification -- Beyond the Capabilities of a Human Observer—0
Sleep Posture One-Shot Learning Framework Using Kinematic Data Augmentation: In-Silico and In-Vivo Case Studies—0
Sorted Pooling in Convolutional Networks for One-shot Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified