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TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
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TZOFFSETTO:+0900
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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035348Z
LOCATION:Room 324\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221208T170000
DTEND;TZID=Asia/Seoul:20221208T183000
UID:siggraphasia_SIGGRAPH Asia 2022_sess167@linklings.com
SUMMARY:Appearance Modeling and Capture
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\nWoven Fabr
 ic Capture from a Single Photo\n\nJin, Wang, Hasan, Guo, Marschner...\n\nD
 igitally reproducing the appearance of woven fabrics is important in many 
 applications of realistic rendering, from interior scenes to virtual chara
 cters. However, designing realistic shading models and capturing real fabr
 ic samples are both challenging tasks. Previous work ranges from applying 
 gen...\n\n---------------------\nMetappearance: Meta-Learning for Visual A
 ppearance Reproduction\n\nFischer, Ritschel\n\nThere currently exist two m
 ain approaches to reproducing visual appearance using Machine Learning (ML
 ): The first is training models that generalize over different instances o
 f a problem, e.g., different images of a dataset. As one-shot approaches, 
 these offer fast inference, but often fall short in...\n\n----------------
 -----\nPivotal Tuning for Latent-based editing of Real Images\n\nRoich, Mo
 kady, Bermano, Cohen-Or\n\nWe bridge the distortion-editability tradeoff i
 n StyleGAN inversion. By slightly altering the generator, an out-of-domain
  image is faithfully mapped into an in-domain latent code. The key idea is
  Pivotal Tuning — a brief training process that preserves the editing qual
 ity of an in-domain laten...\n\n---------------------\nMIPNet: Neural Norm
 al-to-Anisotropic-Roughness MIP mapping\n\nGauthier, Faury, Levallois, Tho
 nat, Thiery...\n\nWe present MIPNet, a novel approach for SVBRDF mipmappin
 g which preserves material appearance under varying view distances and lig
 hting conditions. As in classical mipmapping, our method explicitly encode
 s the multiscale appearance of materials in a SVBRDF mipmap pyramid. To do
  so, we use a tensor-b...\n\n---------------------\nTileGen: Tileable, Con
 trollable Material Generation and Capture\n\nZhou, Hasan, Deschaintre, Gue
 rrero, Sunkavalli...\n\nRecent methods (e.g. MaterialGAN) have used uncond
 itional GANs to generate per-pixel material maps, or as a prior to reconst
 ruct materials from input photographs. These models can generate varied ra
 ndom material appearance, but do not have any mechanism to constrain the g
 enerated material to a speci...\n\n---------------------\nAffine-Transform
 ed Ray Alignment for Fast Ray Traversal\n\nNishidate, Fujishiro\n\nWe prop
 ose affine-transformed ray alignment, an error-free method to accelerate r
 ay traversal by aligning multiple rays into a single ray. This method can 
 reduce time complexity with a simple implementation.\n\n------------------
 ---\nGloss management for consistent reproduction of real and virtual obje
 cts\n\nChen, Piovarci, Wang, Seidel, Didyk...\n\nA good match of material 
 appearance between real-world objects and their digital on-screen represen
 tations is critical for many applications such as fabrication, design, and
  e-commerce. However, faithful appearance reproduction is challenging, esp
 ecially for complex phenomena, such as gloss. In most...\n\n\nRegistration
  Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: I
 N-PERSON, ON-DEMAND
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