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DTSTAMP:20260114T163724Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T123000
DTEND;TZID=Australia/Melbourne:20231213T133600
UID:siggraphasia_SIGGRAPH Asia 2023_sess163@linklings.com
SUMMARY:Motion Synthesis with Awareness
DESCRIPTION:Object Motion Guided Human Motion Synthesis\n\nModeling human 
 behaviors in contextual environments has a wide range of applications in c
 haracter animation, embodied AI, VR/AR, and robotics. In real-world scenar
 ios, humans frequently interact with the environment and manipulate variou
 s objects to complete daily tasks. In this work, we study the p...\n\n\nJi
 aman Li, Jiajun Wu, and Karen Liu (Stanford University)\n-----------------
 ----\nDROP: Dynamics Responses from Human Motion Prior and Projective Dyna
 mics\n\nSynthesizing realistic human movements, dynamically responsive to 
 the environment, is a long-standing objective in character animation, with
  applications in computer vision, sports, and healthcare, for motion predi
 ction and data augmentation. Recent kinematics-based generative motion mod
 els offer im...\n\n\nYifeng Jiang (Stanford University), Jungdam Won (Seou
 l National University), Yuting Ye (Meta Reality Labs Research), and C. Kar
 en Liu (Stanford University)\n---------------------\nMotion to Dance Music
  Generation using Latent Diffusion Model\n\nOur method is a motion-to-musi
 c generation model capable of producing dance music from 3D motion data an
 d genre. It utilizes a latent diffusion-based architecture paired with a p
 re-trained VAE model.\n\n\nVanessa Tan, JungHyun Nam, Juhan Nam, and Junyo
 ng Noh (Korea Advanced Institute of Science and Technology (KAIST))\n-----
 ----------------\nCommonsense Knowledge-Driven Joint Reasoning Approach fo
 r Object Retrieval in Virtual Reality\n\nOut-of-reach object retrieval is 
 an important task in virtual reality (VR). Gesture-based approach, one of 
 the most commonly used approaches, enables bare-hand, eyes-free, and direc
 t retrieval by using assigned gestures. However, it is difficult to retrie
 ve an object from plenty of objects accuratel...\n\n\nHaiyan Jiang (Beijin
 g Institute of Technology; National Key Laboratory of General Artificial I
 ntelligence, Beijing Institute for General Artificial Intelligence (BIGAI)
 ); Dondong Weng (Beijing Institute of Technology); Xiaonuo Dongye (Beijing
  Institute of Technology; National Key Laboratory of General Artificial In
 telligence, Beijing Institute for General Artificial Intelligence (BIGAI))
 ; Le Luo (Beijing Institute of Technology); and Zhenliang Zhang (National 
 Key Laboratory of General Artificial Intelligence, Beijing Institute for G
 eneral Artificial Intelligence (BIGAI))\n---------------------\nSynthDa: E
 xploiting Existing Real-World Data for Usable and Accessible Synthetic Dat
 a Generation\n\nSynthDa: Empowering computer vision with automated synthet
 ic data. Integrating 3 steps, it provides diverse synthetic data from real
 -world datasets for evaluations. Our experiments challenge data quantity b
 eliefs, challenging current beliefs.\n\n\nMegani Rajendran (NVIDIA), Chek 
 Tien Tan and Indriyati Atmosukarto (Singapore Institute of Technology), Ai
 k Beng Ng (NVIDIA), Zhihua Zhou (Singapore Institute of Technology), and A
 ndrew Grant and Simon See (NVIDIA)\n---------------------\nComputational D
 esign of Wiring Layout on Tight Suits with Minimal Motion Resistance\n\nAn
  increasing number of electronics are directly embedded on the clothing to
  monitor human status (skeletal motion or electromyogram activity) or prov
 ide haptic feedback.\nA specific challenge to prototype and fabricate such
  a clothing is to design the wiring layout, to minimize the intervention t
 o h...\n\n\nKai Wang, Xiaoyu Xu, Yinping Zheng, Da Zhou, and Shihui Guo (X
 iamen University); Yipeng Qin (School of Computer Science and Informatic, 
 Cardiff University); and Xiaohu Guo (University of Texas at Dallas)\n\nReg
 istration Category: Full Access\n\nSession Chair: Chek Tien Tan (Singapore
  Institute of Technology, Centre for Immersification)
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