Dual-Path Adaptive Channel Attention Network Based on Feature Constraints for Face Anti-Spoofing
Interference factors in visible light image data, such as backgrounds and lighting, often lead to poor performance of RGB-based single-modality face anti-spoofing methods. To address these limitations, we propose an innovative face anti-spoofing framework. Within this framework, we design a convolut...
Saved in:
Main Authors: | Nana Li, Zhipeng Weng, Fangmei Liu, Zuhe Li, Wei Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10855450/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Frontal Face Generation Based on Attitude Point Guidance and Attention Mechanism Improvement
by: Jihui Zhao, et al.
Published: (2025-01-01) -
Enhancing voice spoofing detection in noisy environments using frequency feature masking augmentation
by: Soyul Han, et al.
Published: (2025-03-01) -
Gradient formulae for probability functions depending on a heterogenous family of constraints
by: van Ackooij, Wim, et al.
Published: (2021-08-01) -
Attention-Based Multi-Learning Approach for Speech Emotion Recognition With Dilated Convolution
by: Samuel, Kakuba, et al.
Published: (2023) -
Masked and unmasked Face Recognition Model Using Deep Learning Techniques. A case of Black Race.
by: Mabiriz,I, Vicent, et al.
Published: (2024)