Fast Sun-aligned Outdoor Scene Relighting based on TensoRF
November 07, 2023 Β· Declared Dead Β· π IEEE Workshop/Winter Conference on Applications of Computer Vision
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Authors
Yeonjin Chang, Yearim Kim, Seunghyeon Seo, Jung Yi, Nojun Kwak
arXiv ID
2311.03965
Category
cs.CV: Computer Vision
Citations
6
Venue
IEEE Workshop/Winter Conference on Applications of Computer Vision
Last Checked
3 months ago
Abstract
In this work, we introduce our method of outdoor scene relighting for Neural Radiance Fields (NeRF) named Sun-aligned Relighting TensoRF (SR-TensoRF). SR-TensoRF offers a lightweight and rapid pipeline aligned with the sun, thereby achieving a simplified workflow that eliminates the need for environment maps. Our sun-alignment strategy is motivated by the insight that shadows, unlike viewpoint-dependent albedo, are determined by light direction. We directly use the sun direction as an input during shadow generation, simplifying the requirements of the inference process significantly. Moreover, SR-TensoRF leverages the training efficiency of TensoRF by incorporating our proposed cubemap concept, resulting in notable acceleration in both training and rendering processes compared to existing methods.
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