High-Dynamic-Range Lighting Estimation from Face Portraits
Sztrajman A, Neophytou A, Weyrich T, Sommerlade E (2020)
Publication Type: Conference contribution
Publication year: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 355-363
Conference Proceedings Title: Proceedings - 2020 International Conference on 3D Vision, 3DV 2020
Event location: Virtual, Fukuoka, JPN
ISBN: 9781728181288
DOI: 10.1109/3DV50981.2020.00045
Abstract
We present a CNN-based method for outdoor highdynamic-range (HDR) environment map prediction from low-dynamic-range (LDR) portrait images. Our method relies on two different CNN architectures, one for light encoding and another for face-to-light prediction. Outdoor lighting is characterised by an extremely high dynamic range, and thus our encoding splits the environment map data between low and high-intensity components, and encodes them using tailored representations. The combination of both network architectures constitutes an end-to-end method for accurate HDR light prediction from faces at real-time rates, inaccessible for previous methods which focused on low dynamic range lighting or relied on non-linear optimisation schemes. We train our networks using both real and synthetic images, we compare our light encoding with other methods for light representation, and we analyse our results for light prediction on real images. We show that our predicted HDR environment maps can be used as accurate illumination sources for scene renderings, with potential applications in 3D object insertion for augmented reality.
Authors with CRIS profile
Involved external institutions
United Kingdom (GB)How to cite
APA:
Sztrajman, A., Neophytou, A., Weyrich, T., & Sommerlade, E. (2020). High-Dynamic-Range Lighting Estimation from Face Portraits. In Proceedings - 2020 International Conference on 3D Vision, 3DV 2020 (pp. 355-363). Virtual, Fukuoka, JPN: Institute of Electrical and Electronics Engineers Inc..
MLA:
Sztrajman, Alejandro, et al. "High-Dynamic-Range Lighting Estimation from Face Portraits." Proceedings of the 8th International Conference on 3D Vision, 3DV 2020, Virtual, Fukuoka, JPN Institute of Electrical and Electronics Engineers Inc., 2020. 355-363.
BibTeX: Download