Frontal Face Generation Based on Attitude Point Guidance and Attention Mechanism Improvement
The deflection of face angle is the most important factor affecting the accuracy in face recognition, non-frontal faces make some face recognition systems lose their due functions, the existing frontal face conversion methods often have the phenomenon of distortion and lack of identity. Aiming at th...
Saved in:
Main Authors: | Jihui Zhao, Zhengyi Yuan, Junhu Zhang, Haitao Li, Hui Li |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10810390/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Profile to frontal face recognition in the wild using coupled conditional generative adversarial network
by: Fariborz Taherkhani, et al.
Published: (2022-05-01) -
Masked and unmasked Face Recognition Model Using Deep Learning Techniques. A case of Black Race.
by: Mabiriz,I, Vicent, et al.
Published: (2024) -
Seeing the Sound: Multilingual Lip Sync for Real-Time Face-to-Face Translation
by: Amirkia Rafiei Oskooei, et al.
Published: (2024-12-01) -
Dual-Path Adaptive Channel Attention Network Based on Feature Constraints for Face Anti-Spoofing
by: Nana Li, et al.
Published: (2025-01-01) -
Robust Face Detection and Identification under Occlusion using MTCNN and RESNET50
by: Eiman Wahab, et al.
Published: (2025-01-01)