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 171–180 of 305 papers

TitleStatusHype
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching—0
Learning to Segment Anatomical Structures Accurately from One Exemplar—0
Leveraging Siamese Networks for One-Shot Intrusion Detection Model—0
AFAT: Adaptive Failure-Aware Tracker for Robust Visual Object Tracking—0
Physics-based polynomial neural networks for one-shot learning of dynamical systems from one or a few samples—0
One-Shot Image Classification by Learning to Restore Prototypes—0
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review—0
Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-MemoryCode0
Meta-Meta Classification for One-Shot LearningCode0
One-Shot GAN Generated Fake Face Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Siamese Neural NetworkAccuracy97.5—Unverified