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BEGIN:VEVENT
DTSTAMP:20230103T035308Z
LOCATION:Room 325-AB\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221207T110000
DTEND;TZID=Asia/Seoul:20221207T123000
UID:siggraphasia_SIGGRAPH Asia 2022_sess161_papers_227@linklings.com
SUMMARY:NeuLighting: Neural Lighting for Free Viewpoint Outdoor Scene Reli
 ghting with Unconstrained Photo Collections
DESCRIPTION:Technical Communications, Technical Papers\n\nNeuLighting: Neu
 ral Lighting for Free Viewpoint Outdoor Scene Relighting with Unconstraine
 d Photo Collections\n\nLi, Guo, Fei, Li, Guo\n\nWe propose NeuLighting, a 
 new framework for free viewpoint outdoor scene relighting from a sparse se
 t of unconstrained in-the-wild photo collections. Our framework represents
  all the scene components as continuous functions parameterized by MLPs th
 at take a 3D location and the lighting condition as input and output refle
 ctance and necessary outdoor illumination properties. Unlike object-level 
 relighting methods which often leverage training images with controllable 
 and consistent indoor illumination, we concentrate on the more challenging
  outdoor situation where all the images are captured under arbitrary unkno
 wn illumination. The key to our method includes a neural lighting represen
 tation that compresses the per-image illumination into a disentangled late
 nt vector, and a new free viewpoint relighting scheme that is robust to ar
 bitrary lighting variations across images. The lighting representation is 
 compressive to explain a wide range of illumination and can be easily fed 
 into the query-based NeuLighting framework, enabling efficient shading eff
 ect evaluation under any kind of novel illumination. Furthermore, to produ
 ce high-quality cast shadows, we estimate the sun visibility map to indica
 te the shadow regions according to the scene geometry and the sun directio
 n. Thanks to the flexible and explainable neural lighting representation, 
 our system supports outdoor relighting with many different illumination so
 urces, including natural images, environment maps, and time-lapse videos. 
 The high-fidelity renderings under novel views and illumination prove the 
 superiority of our method against state-of-the-art relighting solutions.\n
 \nRegistration Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLIS
 H\n\nFormat: IN-PERSON, ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_227&sess=sess16
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