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[VoRF: Volumetric Relightable Faces]

VoRF: Volumetric Relightable Faces

Pramod Rao1,  Mallikarjun B R1,  Gereon Fox1,  Tim Weyrich2,  Bernd Bickel3,  Hans-Peter Seidel1,  Hanspeter Pfister4,  Wojciech Matusik5,  Ayush Tewari5,  Christian Theobalt1,  Mohamed Elgharib1

1 Max Planck Institute for Informatics, Saarbrücken, Germany
2 Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
3 Institute for Science and Technology Austria
4 Harvard University
5 Massachusetts Institute of Technology

Abstract

Portrait viewpoint and illumination editing is an important problem with several applications in VR/AR, movies, and photography. Comprehensive knowledge of geometry and illumination is critical for obtaining photorealistic results. Current methods are unable to explicitly model in 3D while handing both viewpoint and illumination editing from a single image. In this paper, we propose VoRF, a novel approach that can take evena single portrait image as input and relight human heads under novel illuminations that can be viewed from arbitrary viewpoints. VoRF represents a human head as a continuous volumetric field and learns a prior model of human heads using a coordinate-based MLP with individual latent spaces for identity and illumination. The prior model is learnt in an auto-decoder manner over a diverse class of head shapes and appearances, allowing VoRF to generalize to novel test identities from a single input image. Additionally, VoRF has a reflectance MLP that uses the intermediate features of the prior model for rendering One-Light-at-A-Time (OLAT) images under novel views. We synthesize novel illuminations by combining these OLAT images with target environment maps. Qualitative and quantitative evaluations demonstrate the effectiveness of VoRF for relighting and novel view synthesis, even when applied to unseen subjects under uncontrolled illuminations.

Citation Style:    Publication

VoRF: Volumetric Relightable Faces.
Pramod Rao, Mallikarjun B R, Gereon Fox, Tim Weyrich, Bernd Bickel, Hans-Peter Seidel, Hanspeter Pfister, Wojciech Matusik, Ayush Tewari, Christian Theobalt, Mohamed Elgharib.
Invited to International Journal of Computer Vision (IJCV), Springer, 2023.

Related Publications and Reports

[PhotoApp: Photorealistic Appearance Editing of Head Portraits]
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Mallikarjun B R, Ayush Tewari, Abdallah Dib, Tim Weyrich, Bernd Bickel, Hans-Peter Seidel, Hanspeter Pfister, Wojciech Matusik, Louis Chevallier, Mohamed Elgharib, Christian Theobalt.
Transactions on Computer Graphics (Proc. SIGGRAPH), 40(4), 44:1–44:16, July 2021.Mallikarjun B R, Ayush Tewari, Abdallah Dib, Tim Weyrich, Bernd Bickel, Hans-Peter Seidel, Hanspeter Pfister, Wojciech Matusik, Louis Chevallier, Mohamed Elgharib, and Christian Theobalt. PhotoApp: Photorealistic appearance editing of head portraits. In Transactions on Graphics (Proc. SIGGRAPH), volume 40, pages 44:1–44:16, July 2021.B R, M., Tewari, A., Dib, A., Weyrich, T., Bickel, B., Seidel, H.-P., Pfister, H., Matusik, W., Chevallier, L., Elgharib, M., and Theobalt, C. 2021. PhotoApp: Photorealistic appearance editing of head portraits. In Transactions on Graphics (Proc. SIGGRAPH), vol. 40, 44:1–44:16.M. B R, A. Tewari, A. Dib, T. Weyrich, B. Bickel, H.-P. Seidel, H. Pfister, W. Matusik, L. Chevallier, M. Elgharib, and C. Theobalt, “PhotoApp: Photorealistic appearance editing of head portraits,” in Transactions on Graphics (Proc. SIGGRAPH), vol. 40, no. 4, Jul. 2021, pp. 44:1–44:16. [Online]. Available: https://doi.org/10.1145/3450626.3459765
[Web Page][Preprint PDF (14 MB)][BibTeX]
[Monocular Reconstruction of Neural Face Reflectance Fields]
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[Analysis of Human Faces using a Measurement-Based Skin Reflectance Model]
Analysis of Human Faces using a Measurement-Based Skin Reflectance Model.
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[Web Page][PDF][Video][MERL/ETH Skin Reflectance Database][BibTeX]

Acknowledgments

This work was supported by the ERC Consolidator Grant 4DReply (770784).


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