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 201–225 of 305 papers

TitleStatusHype
Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation—0
HalalNet: A Deep Neural Network that Classifies the Halalness Slaughtered Chicken from their Images—0
Learning Relational Representations by Analogy using Hierarchical Siamese Networks—0
Measuring Immediate Adaptation Performance for Neural Machine Translation—0
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences—0
Image Deformation Meta-Networks for One-Shot LearningCode0
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
Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision—0
TET-GAN: Text Effects Transfer via Stylization and Destylization—0
What can I do here? Leveraging Deep 3D saliency and geometry for fast and scalable multiple affordance detectionCode0
That's Mine! Learning Ownership Relations and Norms for Robots—0
Trading robust representations for sample complexity through self-supervised visual experience—0
Unsupervised Meta-Learning For Few-Shot Image Classification—0
Tackling Early Sparse Gradients in Softmax Activation Using Leaky Squared Euclidean Distance—0
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identificationCode0
Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified