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
What Can ResNet Learn Efficiently, Going Beyond Kernels?—0
Few-Shot Adversarial Learning of Realistic Neural Talking Head ModelsCode0
One-Shot Learning for Text-to-SQL Generation—0
Variational Prototyping-Encoder: One-Shot Learning with Prototypical ImagesCode0
OSVNet: Convolutional Siamese Network for Writer Independent Online Signature Verification—0
BAE-NET: Branched Autoencoder for Shape Co-SegmentationCode0
Augmented Memory Networks for Streaming-Based Active One-Shot Learning—0
Similarity Learning Networks for Animal Individual Re-Identification -- Beyond the Capabilities of a Human Observer—0
The Omniglot challenge: a 3-year progress reportCode0
Towards Learning to Imitate from a Single Video Demonstration—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified