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DTSTART:19721003T020000
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BEGIN:VEVENT
DTSTAMP:20240214T070311Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T162500
DTEND;TZID=Australia/Melbourne:20231214T171600
UID:siggraphasia_SIGGRAPH Asia 2023_sess166@linklings.com
SUMMARY:Flesh & Bones
DESCRIPTION:Technical Communications, Technical Papers\n\nLearning Multiva
 riate Empirical Mode Decomposition for Spectral Motion Editing\n\nThis res
 earch proposes an architecture for neural networks to learn multivariate e
 mpirical mode decomposition. Editing the decomposed non-linear frequency c
 omponents achieves novel tasks for character animation synthesis.\n\n\nRan
  Dong (Chukyo University), Soichiro Ikuno (Tokyo University of Technology)
 , and Xi Yang (Jilin University)\n---------------------\nFrom Skin to Skel
 eton : Towards Biomechanically Accurate 3D Digital Humans\n\nGreat progres
 s has been made in estimating 3D human pose and shape from images and vide
 o by training neural networks to directly regress the parameters of parame
 tric human models like SMPL.\nHowever, existing body models have simplifie
 d kinematic structures that do not correspond to accurate joint lo...\n\n\
 nMarilyn Keller (Max Planck Institute for Intelligent Systems), Keenon Wer
 ling (Stanford University), Soyong Shin (Max-Planck-Institut für Informati
 k), Scott Delp (Stanford), Sergi Pujades (INRIA), Karen Liu (Stanford Univ
 ersity), and Michael Black (Max Planck Institute for Intelligent Systems)\
 n---------------------\nRobust Skin Weights Transfer via Weight Inpainting
 \n\nA novel robust method for automated transferring of skin weights betwe
 en meshes with significantly different shapes that surpasses existing comm
 ercial software and research methods.\n\n\nRinat Abdrashitov, Kim Raichsta
 t, Jared Monsen, and David Hill (Epic Games)\n---------------------\nSFLSH
 : Shape-Dependent Soft-Flesh Avatars\n\nWe present a multi-person soft-tis
 sue avatar model. This model maps a body shape descriptor to heterogeneous
  geometric and mechanical parameters of a soft-tissue model across the bod
 y, effectively producing a shape-dependent parametric soft avatar model. T
 he design of the model overcomes two major c...\n\n\nPablo Ramón, Cristian
  Romero, Javier Tapia, and Miguel A. Otaduy (Universidad Rey Juan Carlos)\
 n---------------------\nNeural Motion Graph\n\nDeep learning techniques ha
 ve been employed to design a controllable human motion synthesizer. Despit
 e their potential, however, designing a neural network-based motion synthe
 sis that enables flexible user interaction, fine-grained controllability, 
 and the support of new types of motions at reduced ...\n\n\nHongyu Tao, Sh
 uaiying Hou, Changqing Zou, Hujun Bao, and Weiwei Xu (Zhejiang University)
 \n\nRegistration Category: Full Access\n\nSession Chair: Seungbae Bang (Am
 azon, University of Toronto)
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