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 151–160 of 305 papers

TitleStatusHype
Uncertainty-based Modulation for Lifelong Learning—0
Unsupervised Meta-Learning For Few-Shot Image Classification—0
Unsupervised Noisy Tracklet Person Re-identification—0
Updatable Siamese Tracker with Two-stage One-shot Learning—0
Using Paraphrasing and Memory-Augmented Models to Combat Data Sparsity in Question Interpretation with a Virtual Patient Dialogue System—0
Verbal Programming of Robot Behavior—0
Towards Learning to Imitate from a Single Video Demonstration—0
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks—0
VOCABULARY-INFORMED VISUAL FEATURE AUGMENTATION FOR ONE-SHOT LEARNING—0
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified