Projects per year
Abstract
We introduce InverseFaceNet, a deep convolutional inverse rendering framework for faces that jointly estimates facial pose, shape, expression, reflectance and illumination from a single input image. By estimating all parameters from just a single image, advanced editing possibilities on a single face image, such as appearance editing and relighting, become feasible in real time. Most previous learning-based face reconstruction approaches do not jointly recover all dimensions, or are severely limited in terms of visual quality. In contrast, we propose to recover high-quality facial pose, shape, expression, reflectance and illumination using a deep neural network that is trained using a large, synthetically created training corpus. Our approach builds on a novel loss function that measures model-space similarity directly in parameter space and significantly improves reconstruction accuracy. We further propose a self-supervised bootstrapping process in the network training loop, which iteratively updates the synthetic training corpus to better reflect the distribution of real-world imagery. We demonstrate that this strategy outperforms completely synthetically trained networks. Finally, we show high-quality reconstructions and compare our approach to several state-of-the-art approaches.
Original language | English |
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Title of host publication | 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition |
Publisher | IEEE |
Pages | 4625-4634 |
Number of pages | 10 |
ISBN (Electronic) | 978-1-5386-6421-6 |
DOIs | |
Publication status | Published - 18 Jun 2018 |
Event | International Conference on Computer Vision and Pattern Recognition - Salt Lake City, USA United States Duration: 18 Jun 2018 → 22 Jun 2018 http://cvpr2018.thecvf.com/ |
Publication series
Name | Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) |
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Publisher | IEEE |
ISSN (Print) | 2575-7075 |
Conference
Conference | International Conference on Computer Vision and Pattern Recognition |
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Abbreviated title | CVPR |
Country | USA United States |
City | Salt Lake City |
Period | 18/06/18 → 22/06/18 |
Internet address |
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Projects
- 1 Active
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Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)
Cosker, D., Campbell, N., Fincham Haines, T., Hall, P., Kim, K. I., Lutteroth, C., O'Neill, E., Richardt, C. & Yang, Y.
Engineering and Physical Sciences Research Council
1/09/15 → 28/02/21
Project: Research council