Look More Into Occlusion: Realistic Face Frontalization and Recognition With BoostGAN-Reference-Cited by-同舟云学术

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Look More Into Occlusion: Realistic Face Frontalization and Recognition With BoostGAN

Published:2021-01 Issue:1 Volume:32 Page:214-228
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Duan Qingyan^ORCID,Zhang Lei^ORCID

Funder

National Science Fund of China

Chongqing Natural Science Fund

Chongqing Youth Talent Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/9312808/09042869.pdf?arnumber=9042869

Cited by 38 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Occlusion-Aware Visual-Language Model for Occluded Facial Expression Recognition;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. Facial Recognition System for Law Enforcement: An Integrated Approach Using Haar Cascade Classifier and LBPH Algorithm;2024 International Conference on Advancements in Power, Communication and Intelligent Systems (APCI);2024-06-21

3. ABANet: Attention boundary‐aware network for image segmentation;Expert Systems;2024-05-17

4. Recovery-Based Occluded Face Recognition by Identity-Guided Inpainting;Sensors;2024-01-09

5. Reference-Guided Large-Scale Face Inpainting With Identity and Texture Control;IEEE Transactions on Circuits and Systems for Video Technology;2023-10

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