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DTSTAMP:20260114T163652Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T152000
DTEND;TZID=Australia/Melbourne:20231213T162500
UID:siggraphasia_SIGGRAPH Asia 2023_sess145@linklings.com
SUMMARY:Rendering, Neural Fields & Neural Caches
DESCRIPTION:Discontinuity-Aware 2D Neural Fields\n\nNeural image represent
 ations offer the possibility of high-fidelity, compact storage, and resolu
 tion-independent accuracy, providing an attractive alternative to traditio
 nal pixel and grid-based representations.  \nHowever, coordinate neural ne
 tworks fail to capture discontinuities present in the ima...\n\n\nYash Bel
 he (University of California San Diego); Michael Gharbi, Matt Fisher, and 
 Iliyan Georgiev (Adobe Inc.); and Ravi Ramamoorthi and Tzu-Mao Li (Univers
 ity of California San Diego)\n---------------------\nSeamlessNeRF: Stitchi
 ng Part NeRFs with Gradient Propagation\n\nNeural Radiance Fields (NeRFs) 
 have emerged as a promising representation for 3D scenes, sparking a surge
  in research aimed at extending the editing capabilities in this domain. T
 he task of seamless editing and merging of different NeRFs, similar to the
  "copy-and-paste" function in 2D image editing,...\n\n\nBingchen Gong and 
 Yuehao Wang (The Chinese University of Hong Kong); Xiaoguang Han (Shenzhen
  Research Institute of Big Data, the Chinese University of Hong Kong (Shen
 zhen)); and Qi Dou (The Chinese University of Hong Kong)\n----------------
 -----\nAnalysis and Synthesis of Digital Dyadic Sequences\n\nWe explore th
 e space of matrix-generated $(0, m, 2)$-nets and $(0, 2)$-sequences in bas
 e 2, also known as digital dyadic nets and sequences.\nIn computer graphic
 s, they are arguably leading the competition for use in rendering.\nWe pro
 vide a complete characterization of the design space and count the ...\n\n
 \nAbdalla Ahmed (King Abdullah University of Science and Technology (KAUST
 )) and Mikhail Skopenkov, Markus Hadwiger, and Peter Wonka (KAUST)\n------
 ---------------\nEfficient Visualization of Light Pollution for the Night 
 Sky\n\nThe artificial light sources make our daily life convenient, but th
 ey cause a serious problem called light pollution. \nWe propose a system f
 or efficient visualization of the light pollution for the night sky.\nA nu
 mber of methods have been proposed for rendering the sky, but most of the 
 methods focus...\n\n\nYoshinori Dobashi and Naoto Ishikawa (Hokkaido Unive
 rsity, Prometech CG Research) and Kei Iwasaki (Saitama University, Promete
 ch CG Research)\n---------------------\nNeural Cache for Monte Carlo Parti
 al Differential Equation Solver\n\nThis paper presents a method that uses 
 neural networks as a caching mechanism to reduce the variance of Monte Car
 lo Partial Differential Equation solvers, such as the Walk-on-Spheres algo
 rithm. While these Monte Carlo PDE solvers have the merits of being unbias
 ed and discretization-free, their high ...\n\n\nZilu Li (Cornell Universit
 y); Guandao Yang (Cornell University, Stanford University); and Xi Deng, C
 hristopher De Sa, Bharath Hariharan, and Steve Marschner (Cornell Universi
 ty)\n\nRegistration Category: Full Access\n\nSession Chair: Young J. Kim (
 Ewha Womans University)
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