LMFNet: A Lightweight Multiscale Fusion Network With Hierarchical Structure for Low-Quality 3-D Face Recognition
Author:
Affiliation:
1. Beijing Key Laboratory of Work Safety Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China
2. School of Creative Technologies, University of Portsmouth, Portsmouth, U.K.
Funder
Beijing Natural Science Foundation of China
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Signal Processing,Control and Systems Engineering,Human Factors and Ergonomics
Link
http://xplorestaging.ieee.org/ielx7/6221037/10016745/09874969.pdf?arnumber=9874969
Reference58 articles.
1. Depth as Attention for Face Representation Learning
2. Robust RGB-D Face Recognition Using Attribute-Aware Loss
3. RGB-D face recognition via learning-based reconstruction
4. Deep learning for monocular depth estimation: A review
5. Gesture-Radar: A Dual Doppler Radar Based System for Robust Recognition and Quantitative Profiling of Human Gestures
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1. Depth Map Denoising Network and Lightweight Fusion Network for Enhanced 3D Face Recognition;Pattern Recognition;2024-01
2. DSNet: Dual-stream multi-scale fusion network for low-quality 3D face recognition;AIP Advances;2023-08-01
3. Facial Adversarial Sample Augmentation for Robust Low-Quality 3D Face Recognition;Biometric Recognition;2023
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