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3D Face Reconstruction

Facial Recognition and Modelling › Face Reconstruction › 3D Face Reconstruction 94 평가 기록 9 datasets

3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.

<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>

논문

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

1803.07835 2018-03-21 이 페이지의 평가 3건

Mean NME : 3.7551%

Towards Fast, Accurate and Stable 3D Dense Face Alignment

2009.09960 2020-09-21 이 페이지의 평가 3건

Mean NME: 3.56

3D face reconstruction with dense landmarks

2204.02776 2022-04-06 이 페이지의 평가 2건

RMSE Cooperative: 1.43RMSE Indoor: 1.42RMSE Outdoor: 1.42

Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set

1903.08527 2019-03-20 이 페이지의 평가 2건

RMSE Cooperative: 1.60RMSE Indoor: 1.61

Face Alignment Across Large Poses: A 3D Solution

1511.07212 2015-11-23 이 페이지의 평가 2건

Mean NME : 6.3833%

Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network

1612.04904 2016-12-15 이 페이지의 평가 2건

Average 3D Error: 1.93

Unsupervised Training for 3D Morphable Model Regression

1806.06098 2018-06-15 이 페이지의 평가 2건

Average 3D Error: 1.50

3D Face Morphable Models "In-the-Wild"

1701.05360 2017-01-19 이 페이지의 평가 1건

Average 3D Error: 1.82

ASM: Adaptive Skinning Model for High-Quality 3D Face Modeling

2304.09423 2023-04-19 이 페이지의 평가 1건

RMSE Cooperative: 1.34RMSE Indoor: 1.53

Automated 3D Face Reconstruction From Multiple Images Using Quality Measures

2016-06-01 이 페이지의 평가 1건

RMSE Cooperative: 1.68RMSE Indoor: 1.67

Dense Face Alignment

1709.01442 2017-09-05 이 페이지의 평가 1건

Mean NME : 5.6454%

DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment

2305.11522 2023-05-19 이 페이지의 평가 1건

Mean NME: 3.16

GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction

1902.05978 2019-02-15 이 페이지의 평가 1건

Average 3D Error: 0.95

HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details

2303.11225 2023-03-20 이 페이지의 평가 1건

@nose: 1.036 (±0.280)@mouth: 1.450 (±0.413)@forehead: 1.324 (±0.334)@cheek: 1.291 (±0.362)

Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression

1703.07834 2017-03-22 이 페이지의 평가 1건

Mean NME : 5.2667%

Learning an Animatable Detailed 3D Face Model from In-The-Wild Images

2012.04012 2020-12-07 이 페이지의 평가 1건

Mean Reconstruction Error (mm): 1.91

Learning Free-Form Deformation for 3D Face Reconstruction from In-The-Wild Images

2105.14857 2021-05-31 이 페이지의 평가 1건

Mean NME : 3.51%

Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision

1905.06817 2019-05-16 이 페이지의 평가 1건

Mean Reconstruction Error (mm): 2.08

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

1612.00593 2016-12-02 이 페이지의 평가 1건

0L: po

Pre-training strategies and datasets for facial representation learning

2103.16554 2021-03-30 이 페이지의 평가 1건

Mean NME : 3.42%

SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction

2106.03021 2021-06-06 이 페이지의 평가 1건

Mean NME : 3.25%