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DTSTART:19721003T020000
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BEGIN:VEVENT
DTSTAMP:20240214T070311Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T102000
DTEND;TZID=Australia/Melbourne:20231214T112500
UID:siggraphasia_SIGGRAPH Asia 2023_sess129@linklings.com
SUMMARY:From Pixels to Gradients
DESCRIPTION:Technical Papers\n\nShaDDR: Interactive Example-Based Geometry
  and Texture Generation via 3D Shape Detailization and Differentiable Rend
 ering\n\nWe present ShaDDR, an example-based deep generative neural networ
 k which produces a high-resolution textured 3D shape through geometry deta
 ilization and conditional texture generation applied to an input coarse vo
 xel shape. Trained on a small set of detailed and textured exemplar shapes
 , our method ...\n\n\nQimin Chen, Zhiqin Chen, Hang Zhou, and Hao Zhang (S
 imon Fraser University)\n---------------------\nDR-Occluder: Generating Oc
 cluders using Differentiable Rendering\n\nThe target of the occluder is to
  use very few faces to maintain similar occlusion properties of the origin
 al 3D model.\nIn this paper, we present DR-Occluder, a novel coarse-to-fin
 e framework for occluder generation that leverages differentiable renderin
 g to optimize a triangle set to an occluder. Un...\n\n\nJiaxian Wu, Yue Li
 n, and Dehui Lu (NetEase Games AI Lab)\n---------------------\nDiffusion P
 osterior Illumination for Ambiguity-aware Inverse Rendering\n\nInverse ren
 dering, the process of inferring scene properties from images, is a challe
 nging inverse problem. The task is ill-posed, as many different scene conf
 igurations can give rise to the same image. Most existing solutions incorp
 orate priors into the inverse-rendering pipeline to encourage plaus...\n\n
 \nLinjie Lyu (Max-Planck-Institut für Informatik), Ayush Tewari (MIT CSAIL
 ), Marc Habermann (Max-Planck-Institut für Informatik), Shunsuke Saito and
  Michael Zollhöfer (Reality Labs Research), and Thomas Leimkühler and Chri
 stian Theobalt (Max-Planck-Institut für Informatik)\n---------------------
 \nDifferentiable Rendering of Parametric Geometry\n\nWe propose an efficie
 nt method for differentiable rendering of parametric surfaces and curves, 
 which enables their use in inverse graphics problems. Our central observat
 ion is that a representative triangle mesh can be extracted from a continu
 ous parametric object in a differentiable and efficient w...\n\n\nMarkus W
 orchel and Marc Alexa (TU Berlin)\n---------------------\nTransparent Obje
 ct Reconstruction via Implicit Differentiable Refraction Rendering\n\nReco
 nstructing the geometry of transparent objects has been a long-standing ch
 allenge. Existing methods rely on complex setups, such as manual annotatio
 n or darkroom conditions, to obtain object silhouettes and usually require
  controlled environments with designed patterns to infer ray-background co
 ...\n\n\nFangzhou Gao, Lianghao Zhang, Li Wang, Jiamin Cheng, and Jiawan Z
 hang (Tianjin University)\n\nRegistration Category: Full Access\n\nSession
  Chair: Marc Stamminger (Friedrich-Alexander-Universität Erlangen-Nürnberg
 )
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