Two-Stream Prototype Learning Network for Few-Shot Face Recognition Under Occlusions-Reference-Cited by-同舟云学术

Two-Stream Prototype Learning Network for Few-Shot Face Recognition Under Occlusions

Published:2023 Issue: Volume:25 Page:1555-1563
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Yang Xingyu¹,Han Mengya¹,Luo Yong¹^ORCID,Hu Han²^ORCID,Wen Yonggang³^ORCID

Affiliation:

1. School of Computer Science, National Engineering Research Center for Multimedia Software, Wuhan University, and Hubei Luojia Laboratory, Wuhan, Hubei, China

2. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

3. School of Computer Science and Engineering, Nanyang Technological University, Singapore

Funder

National Key Research and Development Program of China

Special Fund of Hubei Luojia Laboratory

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Media Technology,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6046/10016790/10059188.pdf?arnumber=10059188

Reference53 articles.

1. Prototype Rectification for Few-Shot Learning

2. IFSM: An Iterative Feature Selection Mechanism for Few-Shot Image Classification

3. Crosstransformers: Spatially-aware few-shot transfer;doersch;Proc Adv Neural Inf Process Syst,0

4. Learning class-level prototypes for few-shot learning;yuan,2021

5. ArcFace: Additive Angular Margin Loss for Deep Face Recognition

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