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Joint 3D facial shape reconstruction and texture completion from a single image
2021
Computational Visual Media
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To get the 3D facial geometries, we predict coarse shape (U-V position maps) from the segmented face from the correspondence network using a shape network, and then refine the 3D coarse shape by regressing ...
Then we complete the invisible and occluded areas in the U-V texture map using an inpainting network. ...
We would like to thank Yu Deng et al. for their Deep 3D Face work in 3D face analysis, whose contribution to this field permitted our further study. ...
doi:10.1007/s41095-021-0238-4
fatcat:trtdm3c7ljd3pb7lvxlmxq6dhu
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
[article]
2018
arXiv
pre-print
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To achieve this, we design a 2D representation called UV position map which records the 3D shape of a complete face in UV space, then train a simple Convolutional Neural Network to regress it from a single ...
We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment. ...
We also thank Iacopo Masi for his patience in helping me acquire Florence 3D Face dataset. This work was supported by CloudWalk Technology. ...
arXiv:1803.07835v1
fatcat:sybi46n4wzamvgj72j3u23gpbe
3D Face Recognition
[chapter]
2011
New Approaches to Characterization and Recognition of Faces
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The 3D information (depth and texture maps) corresponding to the surface of the face may be acquired using different alternatives: A multi camera system (stereoscopy), range cameras or 3D laser and scanner ...
This method includes, face finding, landmark finding, and template computation. They used weighted sum rule to fuse shape and texture scores. ...
) , or conformal mapping . ...
doi:10.5772/18696
fatcat:3uoguw3bo5gmlpor63xbid25vy
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
[chapter]
2018
Lecture Notes in Computer Science
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To achieve this, we design a 2D representation called UV position map which records the 3D shape of a complete face in UV space, then train a simple Convolutional Neural Network to regress it from a single ...
We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment. ...
Recently, [28] propose to straightforwardly map the image pixels to full 3D facial structure via volumetric CNN regression. ...
doi:10.1007/978-3-030-01264-9_33
fatcat:ebcqdhdj3jhxph2stxznvcj5ke
3D Dense Face Alignment with Fused Features by Aggregating CNNs and GCNs
[article]
2022
arXiv
pre-print
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In this paper, we propose a novel multi-level aggregation network to regress the coordinates of the vertices of a 3D face from a single 2D image in an end-to-end manner. ...
for the benefit of direct feature learning of 3D face mesh. ...
Most of the facial landmarks localization methods use a joint loss function to guide the training process. ...
arXiv:2203.04643v1
fatcat:toyy4fcrrrg73batvoparlad7u
Real-Time Eye Tracking for Bare and Sunglasses-wearing Faces for Augmented Reality 3D Head-Up Displays
2021
IEEE Access
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RELATED WORK Facial Landmark Detection. Facial landmark localization has been researched for decades. ...
With PFLD, we take the whole face image as input and use fully connection to regress the landmarks. In this way, the connections between different facial components are encoded into the feature maps. ...
doi:10.1109/access.2021.3110644
fatcat:hresfwg3sndvpdahsscqtj2r6a
To Frontalize or Not To Frontalize: Do We Really Need Elaborate Pre-processing To Improve Face Recognition?
[article]
2018
arXiv
pre-print
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To address this question, we evaluate a number of popular facial landmarking and pose correction algorithms to understand their effect on facial recognition performance. ...
CNNs trained using sets of different pre-processing methods are used to extract features from the Point and Shoot Challenge (PaSC) and CMU Multi-PIE datasets. ...
Transformation & Texture Mapping After the fitting process, we use the landmarks S a ∈ R 3N ×1 corresponding to the aligned 3D model I a and the landmarks S r ∈ R 3N ×1 of the generic 3D face model to ...
arXiv:1610.04823v4
fatcat:dqwknkd4cvd6xl2wrosu4h6f2e
High-Fidelity 3D Digital Human Head Creation from RGB-D Selfies
[article]
2021
arXiv
pre-print
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Our 3DMM has much larger expressive capacities than conventional 3DMM, allowing us to recover more accurate facial geometry using merely linear basis. ...
Then a differentiable renderer based 3D Morphable Model (3DMM) fitting algorithm is applied to recover facial geometries from multiview RGB-D data, which takes advantages of a powerful 3DMM basis constructed ...
with the videos; and all the subjects for allowing us to use their selfie data for testing. ...
arXiv:2010.05562v2
fatcat:3b5cil3do5cznpsdur3kwdqf7y
A Multiresolution 3D Morphable Face Model and Fitting Framework
2016
Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
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, face recognition, and, more recently, facial landmark detection and tracking. ...
The model contains different mesh resolution levels and landmark point annotations as well as metadata for texture remapping. ...
Perform a global mapping from the generic model to the target scan using facial landmarks, smoothly deforming the generic model. 3. ...
doi:10.5220/0005669500790086
dblp:conf/visapp/HuberHTMKCRK16
fatcat:tmoyj54udfda3jdt6xfvwtbcgi
Face modeling and editing with statistical local feature control models
2007
International journal of imaging systems and technology (Print)
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The learned control models define a mapping from control parameters back to facial feature shape or texture, thus we can use them to automatically synthesize varied geometric models of human faces. ...
The local feature control models are constructed based on the exemplar 3D face scans. We use a three-step model fitting approach for the 3D registration problem. ...
Region-Based Face Texture Synthesis To synthesize textures of facial features, we form local texture spaces by using PCA. ...
doi:10.1002/ima.20127
fatcat:qd32t6wrfrh2tojjydnietm2ie
Efficient 3D morphable face model fitting
2017
Pattern Recognition
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In addition, we demonstrate its merits in the context of a 3D-assisted 2D face recognition system which detects landmarks automatically and extracts both holistic and local features using a 3DMM. ...
3D face reconstruction of shape and skin texture from a single 2D image can be performed using a 3D Morphable Model (3DMM) in an analysis-by-synthesis approach. ...
Both methods use only facial landmarks to estimate pose and facial shape via an affine camera. They also share the use of spherical harmonics models to estimate illumination. ...
doi:10.1016/j.patcog.2017.02.007
fatcat:mpsnlvokmrehpiw2ylgzu3ik2q
Facial Landmark Machines: A Backbone-Branches Architecture with Progressive Representation Learning
[article]
2018
arXiv
pre-print
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Our proposed BB-FCN generates facial landmark response maps directly from raw images without any preprocessing. ...
Facial landmark localization plays a critical role in face recognition and analysis. ...
Regression-based facial landmark localization methods can be further divided into direct mapping techniques and cascaded regression models. ...
arXiv:1812.03887v1
fatcat:vbwhuk6y4bbzloce2audjnzqrq
3D Aided Face Recognition across Pose Variations
[chapter]
2012
Lecture Notes in Computer Science
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Recently, 3D aided face recognition, concentrating on improving performance of 2D techniques via 3D data, has received increasing attention due to its wide application potential in real condition. ...
It first estimates the face pose based on the Random Regression Forest, and then rotates the 3D face models in the gallery set to that of the probe pose to generate specific gallery sample for matching ...
Fig. 2 , there occurs inevitably some change concerning distribution of points on the facial area, leading to holes on the produced texture map. ...
doi:10.1007/978-3-642-35136-5_8
fatcat:4bw4x7tamren5kgkehkbexnedi
Facial Expression Recognition: A Review of Trends and Techniques
2021
IEEE Access
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Facial Expression Recognition (FER) is presently the aspect of cognitive and affective computing with the most attention and popularity, aided by its vast application areas. ...
The 3D model fitting achieves normalisation in three procedures; (i) fitting a 3D model on a located facial landmark. (ii) Mapping of face texture to the landmarked 3D model. ...
Likewise, [114] synthesised frontal face using 3D Generic Elastic Model (3DDEM) with texture mapping. [115] generate a frontal face from five facial landmark 3D mesh in a single reference. ...
doi:10.1109/access.2021.3113464
fatcat:hapy6t6ohneupiwh7meakzk3ma
Estimation Of Facial Action Intensities On 2D And 3D Data
2011
Zenodo
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However, the Gabor feature extraction is not done directly on 3D surfaces, but on 2D maps of the mean curvature maps computed from 3D data [7] . ...
actions can be used for generating performance-driven facial animations. ...
doi:10.5281/zenodo.42309
fatcat:tnu5y7tp6zcuxp4smrwdbpmczu
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