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 176–200 of 305 papers

TitleStatusHype
TET-GAN: Text Effects Transfer via Stylization and Destylization—0
That's Mine! Learning Ownership Relations and Norms for Robots—0
The Complex Negotiation Dialogue Game—0
The use of large language models to enhance cancer clinical trial educational materials—0
Toward Optimal Run Racing: Application to Deep Learning Calibration—0
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
Using Paraphrasing and Memory-Augmented Models to Combat Data Sparsity in Question Interpretation with a Virtual Patient Dialogue System—0
Verbal Programming of Robot Behavior—0
Towards Learning to Imitate from a Single Video Demonstration—0
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks—0
VOCABULARY-INFORMED VISUAL FEATURE AUGMENTATION FOR ONE-SHOT LEARNING—0
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence—0
Weakly Supervised One-Shot Detection with Attention Similarity Networks—0
What Can ResNet Learn Efficiently, Going Beyond Kernels?—0
One-Shot Learning for Text-to-SQL Generation—0
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified