Face shapenets for 3d face recognition

M Jabberi, A Wali, B Neji, T Beyrouthy, AM Alimi - IEEE Access, 2023‏ - ieeexplore.ieee.org
In this paper, we present a deep learning-based method for 3D face recognition. Unlike
some previous works, our process does not rely on face representation methods as a proxy …

Lmfnet: A lightweight multiscale fusion network with hierarchical structure for low-quality 3-d face recognition

P Zhao, Y Ming, X Meng, H Yu - IEEE Transactions on Human …, 2022‏ - ieeexplore.ieee.org
Three-dimensional (3-D) face recognition (FR) can improve the usability and user-
friendliness of human–machine interaction. In general, 3-D FR can be divided into high …

PointSurFace: Discriminative point cloud surface feature extraction for 3D face recognition

J Yang, Q Li, L Shen - Pattern Recognition, 2024‏ - Elsevier
Due to the geometric information in the 3D face data, the 3D face recognition methods
exhibit better robustness against the physical attacks compared to the 2D recognition …

[HTML][HTML] DSNet: Dual-stream multi-scale fusion network for low-quality 3D face recognition

P Zhao, Y Ming, N Hu, B Lyu, J Zhou - AIP Advances, 2023‏ - pubs.aip.org
3D face recognition (FR) has become increasingly widespread due to the illumination
invariance and pose robustness of 3D face data. Most existing 3D FR methods can only …

Distributional drift adaptation with temporal conditional variational autoencoder for multivariate time series forecasting

H He, Q Zhang, K Yi, K Shi, Z Niu… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Due to the nonstationary nature, the distribution of real-world multivariate time series (MTS)
changes over time, which is known as distribution drift. Most existing MTS forecasting …

Face recognition on point cloud with cgan-top for denoising

J Liu, J Ren, H Sun, X Jiang - ICASSP 2023-2023 IEEE …, 2023‏ - ieeexplore.ieee.org
Face recognition using 3D point clouds is gaining growing interest, while raw point clouds
often contain a significant amount of noise due to imperfect sensors. In this paper, an end-to …

Adaptive representation learning and sample weighting for low-quality 3D face recognition

C Yu, F Sun, Z Zhang, H Li, L Chen, J Sun, Z Xu - Pattern Recognition, 2025‏ - Elsevier
Abstract 3D face recognition (3DFR) algorithms have advanced significantly in the past two
decades by leveraging facial geometric information, but they mostly focus on high-quality 3D …

CG-MCFNet: cross-layer guidance-based multi-scale correlation fusion network for 3D face recognition

P Zhao, Y Ming, H Yu, Y Hu, J Zhou, Y Liu - Applied Intelligence, 2025‏ - Springer
Abstract 3D face recognition (FR) has been a popular field in recent years, which benefits
from the advancement of 3D sensors and the application demands of video surveillance …

Facial adversarial sample augmentation for robust low-quality 3D face recognition

F Sun, C Yu, H Li - Chinese Conference on Biometric Recognition, 2023‏ - Springer
Compared with traditional 3D face recognition tasks using high precision 3D face scans, 3D
face recognition based on low-quality data captured by consumer depth cameras is more …

3D Face Recognition on Low-Quality Data via Dual Contrastive Learning

Y **g, D Shao, S Gao, X Lu - 2024 International Conference …, 2024‏ - ieeexplore.ieee.org
3D face recognition has recently gained substantial attention. While many deep learning-
based techniques have achieved impressive results with high-quality datasets, recognizing …