Work

RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection

Year: 2019

Type: conference-paper

Source: IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings

DOI: 10.1109/cvpr.2019.00534

Authors: Leonid Karlinsky, Joseph Shtok, Sivan Harary, Eli Schwartz, Amit Aides, Rogerio Feris, Raja Giryes, Alex M. Bronstein

Institutions: IBM (United States), Tel Aviv University, Massachusetts Institute of Technology, Technion – Israel Institute of Technology

Language: English

Topic: Domain Adaptation and Few-Shot Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W2962837320

FWCI: 20.12

Cites: 68

Cited by: 407

Related to: 10