A Deeper Analysis of Volumetric Relightiable Faces
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11263_2023_Article_1899.pdf
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Author(s)
Rao, Pramod
Mallikarjun, B. R.
Fox, Gereon
Weyrich, Tim
Bickel, Bernd
Pfister, Hanspeter
Matusik, Wojciech
Zhan, Fangneng
Tewari, Ayush
Theobalt, Christian
Date Issued
October 31, 2023
Publisher
Springer US
Citation
Rao, Pramod, Mallikarjun, B. R., Fox, Gereon, Weyrich, Tim, Bickel, Bernd et al. 2023. "A Deeper Analysis of Volumetric Relightiable Faces."
Version
Final published version
Abstract
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 handling both viewpoint and illumination editing from a single image. In this paper, we propose VoRF, a novel approach that can take even a 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 learned 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 illumination. This work is an extension of Rao et al. (VoRF: Volumetric Relightable Faces 2022). We provide extensive evaluation and ablative studies of our model and also provide an application, where any face can be relighted using textual input.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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DOI of Published Version
https://doi.org/10.1007/s11263-023-01899-3
