Lite2Relight: 3D-aware Single Image Portrait Relighting
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Date
2024-07
Publication Type
Conference Paper
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yes
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Abstract
Achieving photorealistic 3D view synthesis and relighting of human portraits is pivotal for advancing AR/VR applications. Existing methodologies in portrait relighting demonstrate substantial limitations in terms of generalization and 3D consistency, coupled with inaccuracies in physically realistic lighting and identity preservation. Furthermore, personalization from a single view is difficult to achieve and often requires multiview images during the testing phase or involves slow optimization processes. This paper introduces Lite2Relight, a novel technique that can predict 3D consistent head poses of portraits while performing physically plausible light editing at interactive speed. Our method uniquely extends the generative capabilities and efficient volumetric representation of EG3D, leveraging a lightstage dataset to implicitly disentangle face reflectance and perform relighting under target HDRI environment maps. By utilizing a pre-trained geometry-aware encoder and a feature alignment module, we map input images into a relightable 3D space, enhancing them with a strong face geometry and reflectance prior. Through extensive quantitative and qualitative evaluations, we show that our method outperforms the state-of-the-art methods in terms of efficacy, photorealism, and practical application. This includes producing 3D-consistent results of the full head, including hair, eyes, and expressions. Lite2Relight paves the way for large-scale adoption of photorealistic portrait editing in various domains, offering a robust, interactive solution to a previously constrained problem.
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Publication status
published
External links
Book title
SIGGRAPH '24: ACM SIGGRAPH 2024 Conference Papers
Journal / series
Volume
Pages / Article No.
41
Publisher
Association for Computing Machinery
Event
ACM SIGGRAPH 2024 Conference (SIGGRAPH 2024)
Edition / version
Methods
Software
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Date collected
Date created
Subject
Faces; Relighting; Volumetric Representation; Generative Modeling
Organisational unit
09809 - Bickel, Bernd / Bickel, Bernd