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DTSTAMP:20260114T163710Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T152000
DTEND;TZID=Australia/Melbourne:20231213T162500
UID:siggraphasia_SIGGRAPH Asia 2023_sess125@linklings.com
SUMMARY:Light, Shadows & Curves
DESCRIPTION:Shadow Harmonization for Realistic Compositing\n\nCompositing 
 virtual objects into real background images requires one to carefully matc
 h the scene's camera parameters, surface geometry, textures, and lighting 
 to obtain plausible renderings.\nRecent learning approaches have shown man
 y scene properties can be estimated from images, resulting in robus...\n\n
 \nLucas Valença and Jinsong Zhang (Université Laval), Michaël Gharbi and Y
 annick Hold-Geoffroy (Adobe), and Jean-François Lalonde (Université Laval)
 \n---------------------\nReShader: View-Dependent Highlights for Single Im
 age View-Synthesis\n\nIn recent years, novel view synthesis from a single 
 image has seen significant progress thanks to the rapid advancements in 3D
  scene representation and image inpainting techniques. While the current a
 pproaches are able to synthesize geometrically consistent novel views, the
 y often do not handle the ...\n\n\nAvinash Paliwal and Brandon G. Nguyen (
 Texas A&M University), Andrii Tsarov (Leia Inc.), and Nima Khademi Kalanta
 ri (Texas A&M University)\n---------------------\nSOL-NeRF: Sunlight Model
 ing for Outdoor Scene Decomposition and Relighting\n\nOutdoor scenes often
  involve large-scale geometry and complex unknown lighting conditions, mak
 ing it difficult to decompose them into geometry, reflectance and illumina
 tion. Recently researchers made attempts to decompose outdoor scenes using
  Neural Radiance Fields (NeRF) and learning-based lighting...\n\n\nJia-Mu 
 Sun and Tong Wu (Institute of Computing Technology, Chinese Academy of Sci
 ences; University of Chinese Academy of Sciences); Yong-Liang Yang (Univer
 sity of Bath); Yu-Kun Lai (Cardiff University); and Lin Gao (Institute of 
 Computing Technology, Chinese Academy of Sciences; University of Chinese A
 cademy of Sciences)\n---------------------\nSpatiotemporally Consistent HD
 R Indoor Lighting Estimation\n\nWe propose a physically-motivated deep lea
 rning framework to solve a general version of the challenging indoor light
 ing estimation problem. Given a single LDR image with a depth map, our met
 hod predicts spatially consistent lighting at any given image position. Pa
 rticularly, when the input is an LDR...\n\n\nZhengqin Li (Meta, University
  of California San Diego); Yu Li and Mikhail Okunev (Meta); Manmohan Chand
 raker (University of California San Diego); and Zhao Dong (Meta)\n--------
 -------------\nAn Adaptive Fast-Multipole-Accelerated Hybrid Boundary Inte
 gral Equation Method for Accurate Diffusion Curves\n\nIn theory, diffusion
  curves promise complex color gradations for infinite-resolution vector gr
 aphics. In practice, existing realizations suffer from poor scaling, discr
 etization artifacts, or insufficient support for rich boundary conditions.
  Previous applications of the boundary element method to d...\n\n\nSeungba
 e Bang (University of Toronto, Amazon); Kirill Serkh (University of Toront
 o); Oded Stein (University of Southern California, MIT); and Alec Jacobson
  (University of Toronto, Adobe)\n\nRegistration Category: Full Access\n\nS
 ession Chair: Michael Gharbi (Reve AI, Massachusetts Institute of Technolo
 gy (MIT))
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