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Face shapenets for 3d face recognition
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 …
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
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 …
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
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 …
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
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 …
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
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 …
changes over time, which is known as distribution drift. Most existing MTS forecasting …
Face recognition on point cloud with cgan-top for denoising
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 …
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
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 …
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
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 …
from the advancement of 3D sensors and the application demands of video surveillance …
Facial adversarial sample augmentation for robust low-quality 3D face recognition
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 …
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
3D face recognition has recently gained substantial attention. While many deep learning-
based techniques have achieved impressive results with high-quality datasets, recognizing …
based techniques have achieved impressive results with high-quality datasets, recognizing …