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 201–210 of 305 papers

TitleStatusHype
Measuring Immediate Adaptation Performance for Neural Machine Translation—0
MemGEN: Memory is All You Need—0
Memory Matching Networks for One-Shot Image Recognition—0
Metalearning with Hebbian Fast Weights—0
Modeling Time Series Similarity with Siamese Recurrent Networks—0
More than the Sum of Its Parts: Ensembling Backbone Networks for Few-Shot Segmentation—0
Multi-Attention Network for One Shot Learning—0
Multimodal Continuation-style Architectures for Human-Robot Interaction—0
MU-MAE: Multimodal Masked Autoencoders-Based One-Shot Learning—0
Npix2Cpix: A GAN-Based Image-to-Image Translation Network With Retrieval- Classification Integration for Watermark Retrieval From Historical Document Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified