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
Unsupervised Noisy Tracklet Person Re-identification—0
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks—0
Better Together: Resnet-50 accuracy with 13 fewer parameters and at 3 speed—0
One-Shot Learning with Triplet Loss for Vegetation Classification Tasks—0
Robust One Shot Audio to Video Generation—0
Contour Transformer Network for One-shot Segmentation of Anatomical StructuresCode0
Depression Status Estimation by Deep Learning based Hybrid Multi-Modal Fusion Model—0
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Resource Constrained Dialog Policy Learning via Differentiable Inductive Logic Programming—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified