Imface: A nonlinear 3d morphable face model with implicit neural representations

M Zheng, H Yang, D Huang… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Precise representations of 3D faces are beneficial to various computer vision and graphics
applications. Due to the data discretization and model linearity however, it remains …

Instant multi-view head capture through learnable registration

T Bolkart, T Li, MJ Black - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Existing methods for capturing datasets of 3D heads in dense semantic correspondence are
slow and commonly address the problem in two separate steps; multi-view stereo (MVS) …

3D statistical head modeling for face/head-related product design: a state-of-the-art review

J Zhang, Y Luximon, P Shah, P Li - Computer-Aided Design, 2023 - Elsevier
In the field of face/head-related product design, 3D statistical models (3DSMs) of human
heads and faces are widely used to model geometric variations, generate representative …

Static and motion facial analysis for craniofacial assessment and diagnosing diseases

H Matthews, G de Jong, T Maal… - Annual Review of …, 2022 - annualreviews.org
Deviation from a normal facial shape and symmetry can arise from numerous sources,
including physical injury and congenital birth defects. Such abnormalities can have …

3dmm-rf: Convolutional radiance fields for 3d face modeling

S Galanakis, B Gecer, A Lattas… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Facial 3D Morphable Models are a main computer vision subject with countless
applications and have been highly optimized in the last two decades. The tremendous …

4D facial analysis: A survey of datasets, algorithms and applications

YJ Liu, B Wang, L Gao, J Zhao, R Yi, M Yu, Z Pan… - Computers & …, 2023 - Elsevier
Facial information plays an important role in human communication, eg, rich and nuanced
facial expressions effectively convey emotions. Traditional data such as 2D facial images …

Toward mesh-invariant 3d generative deep learning with geometric measures

T Besnier, S Arguillère, E Pierson, M Daoudi - Computers & Graphics, 2023 - Elsevier
Abstract 3D generative modeling is accelerating as the technology allowing the capture of
geometric data is developing. However, the acquired data is often inconsistent, resulting in …

Deep Learning in Fringe Projection: a Review

H Liu, N Yan, B Shao, S Yuan, X Zhang - Neurocomputing, 2024 - Elsevier
Fringe projection is widely recognized as a prominent technique for 3D measurement, owing
to its non-contact nature, high precision, and exceptional spatial resolution. However, it …

Towards fine-grained optimal 3d face dense registration: An iterative dividing and diffusing method

Z Fan, S Peng, S Xia - International Journal of Computer Vision, 2023 - Springer
Dense vertex-to-vertex correspondence (ie registration) between 3D faces is a fundamental
and challenging issue for 3D &2D face analysis. While the sparse landmarks are definite …

Learning implicit functions for dense 3D shape correspondence of generic objects

F Liu, X Liu - IEEE Transactions on Pattern Analysis and …, 2023 - ieeexplore.ieee.org
The objective of this paper is to learn dense 3D shape correspondence for topology-varying
generic objects in an unsupervised manner. Conventional implicit functions estimate the …