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 181–190 of 305 papers

TitleStatusHype
Towards Consistent Video Editing with Text-to-Image Diffusion Models—0
Towards Generalizable Sentence Embeddings—0
Towards one-shot learning for rare-word translation with external experts—0
Towards Robust Drone Vision in the Wild—0
Trading robust representations for sample complexity through self-supervised visual experience—0
Transductive One-Shot Learning Meet Subspace Decomposition—0
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified