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TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035348Z
LOCATION:Room 325-AB\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221208T140000
DTEND;TZID=Asia/Seoul:20221208T153000
UID:siggraphasia_SIGGRAPH Asia 2022_sess169@linklings.com
SUMMARY:Rendering Systems
DESCRIPTION:Technical Communications, Technical Papers\n\nThe presentation
 s will be followed by a 30-min Interactive Discussion Session at Room 325-
 CD.\n\nThe Technical Papers program is the premier international forum for
  disseminating new scholarly work in computer graphics and interactive tec
 hniques. Technical Papers are published as a special issue of ACM Transact
 ions on Graphics. In addition to papers selected by the SIGGRAPH Asia 2022
  Technical Papers Jury, the conference presents papers that have been publ
 ished in ACM Transactions on Graphics during the past year. Accepted paper
 s adhere to the highest scientific standards.\n\nThe Technical Communicati
 ons program is a premier forum for presenting the latest developments and 
 research still in progress. Leading international experts in academia and 
 industry present work that showcase actual implementations of research ide
 as, works at the crossroads of computer graphics with computer vision, mac
 hine learning, HCI, VR, CAD, visualization, and many others.\n\nTauray: A 
 Scalable Real-Time Open-Source Path Tracer for Stereo and Light Field Disp
 lays\n\nIkkala, Mäkitalo, Lauttia, Leria, Jääskeläinen\n\nTauray is a new 
 open-source, real-time path tracer targeting stereo and light field displa
 ys. It's based on cross-platform APIs and can utilize ray tracing hardware
  acceleration and multiple GPUs.\n\n---------------------\nHuman Performan
 ce Modeling and Rendering via Neural Animated Mesh\n\nZhao, Jiang, Yao, Zh
 ang, Wang...\n\nWe have recently seen tremendous progress in the neural ad
 vances for photo-real human modeling and rendering. But it's still challen
 ging to integrate them into an existing mesh-based pipeline for downstream
  applications. In this paper, we present a comprehensive neural approach f
 or high-quality reco...\n\n---------------------\nNeural Parameterization 
 for Dynamic Human Head Editing\n\nMa, Li, Liao, Wang, Zhang...\n\nImplicit
  radiance functions emerged as a powerful scene representation for reconst
 ructing and rendering photo-realistic views of a 3D scene. These represent
 ations, however, suffer from poor editability. On the other hand, explicit
  representations such as polygonal meshes allow easy editing, but are ...\
 n\n---------------------\nQuadStream: A Quad-Based Scene Streaming Archite
 cture for Novel Viewpoint Reconstruction\n\nHladky, Stengel, Vining, Kerbl
 , Seidel...\n\nCloud rendering is attractive when targeting thin client de
 vices such as phones or VR/AR headsets, or any situation where a high-end 
 GPU is not available due to thermal or power constraints. However, it intr
 oduces the challenge of streaming rendered data over a network in a manner
  that is robust to ...\n\n---------------------\nICARUS: A Specialized Arc
 hitecture for Neural Radiance Fields Rendering\n\nRao, Yu, Wan, Zhou, Zhen
 g...\n\nThe practical deployment of Neural Radiance Fields (NeRF) in rende
 ring applications faces several challenges, with the most critical one bei
 ng low rendering speed on even high-end graphic processing units (GPUs). I
 n this paper, we present ICARUS, a specialized accelerator architecture ta
 ilored for N...\n\n---------------------\nLearning to Relight Portrait Ima
 ges via a Virtual Light Stage and Synthetic-to-Real Adaptation\n\nYeh, Nag
 ano, Khamis, Kautz, Liu...\n\nGiven a portrait image of a person and an en
 vironment map of the target lighting, portrait relighting aims to re-illum
 inate the person in the image as if the person appeared in an environment 
 with the target lighting. To achieve high-quality results, recent methods 
 rely on deep learning. An effectiv...\n\n---------------------\nLuisaRende
 r: A High-Performance Rendering Framework with Layered and Unified Interfa
 ces on Stream Architectures\n\nZheng, Zhou, Chen, Yan, Zhang...\n\nThe adv
 ancements in hardware have drawn more attention than ever to high-quality 
 offline rendering with modern stream processors, both in the industry and 
 in research fields. However, the graphics APIs are fragmented and existing
  shading languages lack high-level constructs such as polymorphism, whi...
 \n\n\nRegistration Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: EN
 GLISH\n\nFormat: IN-PERSON, ON-DEMAND
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