Fast Sun-aligned Outdoor Scene Relighting based on TensoRF
Yeonjin Chang Yearim Kim Seunghyeon Seo Jung Yi Nojun Kwak
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.