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 101–110 of 305 papers

TitleStatusHype
A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationshipsCode0
AROS: Affordance Recognition with One-Shot Human Stances—0
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition—0
MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layersCode0
One-shot Detail Retouching with Patch Space Neural Transformation BlendingCode0
One-Shot Learning of Stochastic Differential Equations with Data Adapted Kernels—0
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition—0
Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot ClassificationCode0
A System For Robot Concept Learning Through Situated Dialogue—0
Towards Robust Drone Vision in the Wild—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified