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DTSTART:19700308T020000
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DTSTAMP:20260417T190102Z
LOCATION:West Building\, Rooms 301-305
DTSTART;TZID=America/Los_Angeles:20250812T104500
DTEND;TZID=America/Los_Angeles:20250812T121500
UID:siggraph_SIGGRAPH 2025_sess115@linklings.com
SUMMARY:Illuminating Light
DESCRIPTION:WishGI: Lightweight Static Global Illumination Baking via Sphe
 rical Harmonics Fitting\n\nOur work is a lightweight static global illumin
 ation baking solution that achieves competitive lighting effects while usi
 ng only approximately 5% of the memory required by mainstream industry tec
 hniques. By adopting a vertex-probe structure, we ensure excellent runtime
  performance, making it suitabl...\n\n\nJunke Zhu (University of Science a
 nd Technology of China, Tencent Technology); Zehan Wu (Tencent Technology)
 ; Qixing Zhang (University of Science and Technology of China); Cheng Liao
  (Tencent Technology); and Zhangjin Huang (University of Science and Techn
 ology of China)\n---------------------\nRenderFormer: Transformer-based Ne
 ural Rendering of Triangle Meshes with Global Illumination\n\nWe present R
 enderFormer, a neural rendering pipeline that directly renders an image fr
 om a triangle-based representation of scene with full global illumination 
 effects, and that does not require per-scene training or finetuning.\n\n\n
 Chong Zeng (State Key Lab of CAD and CG, Zhejiang University; Microsoft Re
 search Asia); Yue Dong (Microsoft Research Asia); Pieter Peers (College of
  William & Mary); Hongzhi Wu (State Key Lab of CAD and CG, Zhejiang Univer
 sity); and Xin Tong (Microsoft Research Asia)\n---------------------\nDual
 -Band Feature Fusion for Neural Global Illumination with Multi-Frequency R
 eflections\n\nWe present a neural global illumination method capable of ca
 pturing multi-frequency reflections in dynamic scenes by leveraging object
 -centric feature grids and a novel dual-band fusion module. Our approach p
 roduces high-quality, realistic rendering effects and outperforms state-of
 -the-art technique...\n\n\nShaohua Mo, Chuankun Zheng, Zihao Lin, and Dian
 bing Xi (State Key Lab of CAD&CG, Zhejiang University); Qi Ye (Zhejiang Un
 iversity); Rui Wang and Hujun Bao (State Key Lab of CAD&CG, Zhejiang Unive
 rsity); and Yuchi Huo (State Key Lab of CAD&CG, Zhejiang University; Zheji
 ang Lab)\n---------------------\nSegment-based Light Transport Simulation\
 n\nWe introduce a novel segment-based framework for light transport simula
 tion, efficiently assembling paths from disconnected segments. Our method 
 includes innovative segment sampling techniques and corresponding estimati
 on strategies. To demonstrate its strengths, we propose a robust bidirecti
 onal pa...\n\n\nWenyou Wang (University of Waterloo), Rex West (Aoyama Gak
 uin University), and Toshiya Hachisuka (University of Waterloo)\n---------
 ------------\nNeural Importance Sampling of Many Lights\n\nNeural approach
  for estimating spatially varying light selection distributions to improve
  importance sampling in Monte Carlo rendering. To efficiently manage hundr
 eds or thousands of lights, we integrate our neural approach with light hi
 erarchy techniques, where the network predicts cluster-level di...\n\n\nPe
 dro Figueiredo and Qihao He (Texas A&M University), Steve Bako (Aurora Inn
 ovation), and Nima Khademi Kalantari (Texas A&M University)\n-------------
 --------\nIlluminating Light - Interactive Discussion\n\nAfter the summary
  presentations, attendees will participate in an interactive discussion. O
 utside the room will be a series of poster boards for authors to gather ar
 ound with the audience. Authors are invited to bring any material related 
 to their paper that could instigate further conversation such...\n\n------
 ---------------\nGaussian Compression for Precomputed Indirect Illuminatio
 n\n\nWe propose a Gaussian fitting compression method for light field prob
 es, reducing storage and memory demands in large scenes. Using low-bit ada
 ptive Gaussians and GPU-accelerated decompression, our technique replaces 
 traditional PCA-based approaches, achieving 1:50 compression ratios. Real-
 time casc...\n\n\nZhi Zhou (Tencent, University of Science and Technology 
 of China); Chao Li, Zhenyuan Zhang, Mingcong Tang, Zibin Li, and Shuhang L
 uan (Tencent); and Zhangjin Huang (University of Science and Technology of
  China)\n\nInterest Area: Research & Education\n\nRecording: Livestreamed,
  Not Livestreamed, Recorded, Not Recorded\n\nRegistration Category: Full C
 onference, Virtual Access, Tuesday\n\nSession Chair: Chris Wyman (NVIDIA)
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