3D Face Reconstruction by Learning from Synthetic Data
- 1 October 2016
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 460-469
- https://doi.org/10.1109/3dv.2016.56
Abstract
Fast and robust three-dimensional reconstruction of facial geometric structure from a single image is a challenging task with numerous applications. Here, we introduce a learning-based approach for reconstructing a three-dimensional face from a single image. Recent face recovery methods rely on accurate localization of key characteristic points. In contrast, the proposed approach is based on a Convolutional-Neural-Network (CNN) which extracts the face geometry directly from its image. Although such deep architectures outperform other models in complex computer vision problems, training them properly requires a large dataset of annotated examples. In the case of three-dimensional faces, currently, there are no large volume data sets, while acquiring such big-data is a tedious task. As an alternative, we propose to generate random, yet nearly photo-realistic, facial images for which the geometric form is known. The suggested model successfully recovers facial shapes from real images, even for faces with extreme expressions and under various lighting conditions.Keywords
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This publication has 16 references indexed in Scilit:
- Human Pose Estimation with Iterative Error FeedbackPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Large-Pose Face Alignment via CNN-Based Dense 3D Model FittingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- One millisecond face alignment with an ensemble of regression treesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Face Alignment at 3000 FPS via Regressing Local Binary FeaturesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Extensive Facial Landmark Localization with Coarse-to-Fine Convolutional Network CascadePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- 3D Face Reconstruction from a Single Image Using a Single Reference Face ShapeIEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
- Bosphorus Database for 3D Face AnalysisLecture Notes in Computer Science, 2008
- Lambertian reflectance and linear subspacesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2003
- A morphable model for the synthesis of 3D facesPublished by Association for Computing Machinery (ACM) ,1999
- Illumination for computer generated picturesCommunications of the ACM, 1975