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

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Showing 151–160 of 305 papers

TitleStatusHype
DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations—0
One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information ExtractionCode1
Grounded Language Learning Fast and SlowCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
Exploiting Temporal Coherence for Self-Supervised One-shot Video Re-identification—0
Sorted Pooling in Convolutional Networks for One-shot Learning—0
One-Shot Learning for Language ModellingCode1
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching—0
Learning to Segment Anatomical Structures Accurately from One Exemplar—0
Anatomical Data Augmentation via Fluid-based Image RegistrationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified