[HTML][HTML] Survey on 3D face reconstruction from uncalibrated images

A Morales, G Piella, FM Sukno - Computer Science Review, 2021 - Elsevier
Recently, a lot of attention has been focused on the incorporation of 3D data into face
analysis and its applications. Despite providing a more accurate representation of the face …

Ganfit: Generative adversarial network fitting for high fidelity 3d face reconstruction

B Gecer, S Ploumpis, I Kotsia… - Proceedings of the …, 2019 - openaccess.thecvf.com
In the past few years, a lot of work has been done towards reconstructing the 3D facial
structure from single images by capitalizing on the power of Deep Convolutional Neural …

Wing loss for robust facial landmark localisation with convolutional neural networks

ZH Feng, J Kittler, M Awais… - Proceedings of the …, 2018 - openaccess.thecvf.com
We present a new loss function, namely Wing loss, for robust facial landmark localisation
with Convolutional Neural Networks (CNNs). We first compare and analyse different loss …

3d morphable face models—past, present, and future

B Egger, WAP Smith, A Tewari, S Wuhrer… - ACM Transactions on …, 2020 - dl.acm.org
In this article, we provide a detailed survey of 3D Morphable Face Models over the 20 years
since they were first proposed. The challenges in building and applying these models …

Fast-ganfit: Generative adversarial network for high fidelity 3d face reconstruction

B Gecer, S Ploumpis, I Kotsia, S Zafeiriou - arXiv preprint arXiv …, 2021 - arxiv.org
A lot of work has been done towards reconstructing the 3D facial structure from single
images by capitalizing on the power of Deep Convolutional Neural Networks (DCNNs). In …

Photo-realistic facial details synthesis from single image

A Chen, Z Chen, G Zhang… - Proceedings of the …, 2019 - openaccess.thecvf.com
We present a single-image 3D face synthesis technique that can handle challenging facial
expressions while recovering fine geometric details. Our technique employs expression …

Frankenstein: Learning deep face representations using small data

G Hu, X Peng, Y Yang, TM Hospedales… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Deep convolutional neural networks have recently proven extremely effective for difficult
face recognition problems in uncontrolled settings. To train such networks, very large …

Joint face alignment and 3D face reconstruction with application to face recognition

F Liu, Q Zhao, X Liu, D Zeng - IEEE transactions on pattern …, 2018 - ieeexplore.ieee.org
Face alignment and 3D face reconstruction are traditionally accomplished as separated
tasks. By exploring the strong correlation between 2D landmarks and 3D shapes, in contrast …

Dynamic attention-controlled cascaded shape regression exploiting training data augmentation and fuzzy-set sample weighting

ZH Feng, J Kittler, W Christmas… - Proceedings of the …, 2017 - openaccess.thecvf.com
We present a new Cascaded Shape Regression (CSR) architecture, namely Dynamic
Attention-Controlled CSR (DAC-CSR), for robust facial landmark detection on unconstrained …

[HTML][HTML] Gaussian mixture 3D morphable face model

P Koppen, ZH Feng, J Kittler, M Awais, W Christmas… - Pattern Recognition, 2018 - Elsevier
Abstract 3D Morphable Face Models (3DMM) have been used in pattern recognition for
some time now. They have been applied as a basis for 3D face recognition, as well as in an …