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DTSTAMP:20260817T171539Z
LOCATION:Hall B7 (1)\, B Block\, Level 7
DTSTART;TZID=Asia/Tokyo:20241205T130000
DTEND;TZID=Asia/Tokyo:20241205T141000
UID:siggraphasia_SIGGRAPH Asia 2024_sess132@linklings.com
SUMMARY:Characters and Crowds
DESCRIPTION:Each Paper gives a 10 minute presentation.\n\nPDP: Physics-Bas
 ed Character Animation via Diffusion Policy\n\nGenerating diverse and real
 istic human motion that can physically interact with an environment remain
 s a challenging research area in character animation. Meanwhile, diffusion
 -based methods, as proposed by the robotics community, have demonstrated t
 he ability to capture highly diverse and multi-moda...\n\n\nTakara Truong,
  Michael Piseno, Zhaoming Xie, and Karen Liu (Stanford University)\n------
 ---------------\nMonkey See, Monkey Do: Harnessing Self-attention in Motio
 n Diffusion for Zero-shot Motion Transfer\n\nGiven the remarkable results 
 of motion synthesis with diffusion models, a natural question arises: how 
 can we effectively leverage these models for motion editing? Existing diff
 usion-based motion editing methods overlook the profound potential of the 
 prior embedded within the weights of pre-trained ...\n\n\nSigal Raab, Inba
 r Gat, Nathan Sala, Guy Tevet, and Rotem Shalev-Arkushin (Tel Aviv Univers
 ity); Ohad Fried (Reichman University); and Amit Haim Bermano and Daniel C
 ohen-Or (Tel Aviv University)\n---------------------\nCBIL: Collective Beh
 avior Imitation Learning for Fish from Real Videos\n\nReproducing realisti
 c collective behaviors presents a captivating yet formidable challenge. Tr
 aditional rule-based methods rely on hand-crafted principles, limiting mot
 ion diversity and realism in generated collective behaviors. Recent imitat
 ion learning methods learn from data but often require gro...\n\n\nYifan W
 u (University of Hong Kong); Zhiyang Dou (University of Hong Kong, Univers
 ity of Pennsylvania); Yuko Ishiwaka and Shun Ogawa (SoftBank); Yuke Lou (U
 niversity of Hong Kong); Wenping Wang (Texas A&M University); Lingjie Liu 
 (University of Pennsylvania); and Taku Komura (University of Hong Kong)\n-
 --------------------\nResolving Collisions in Dense 3D Crowd Animations\n\
 nWe propose a contact-aware method for synthesizing dense 3D crowds of ani
 mated characters. Unlike existing methods, our approach prevents character
  intersections by modeling contacts using physics-based techniques. This r
 esults in real-time, collision-free animations with enhanced realism and g
 eomet...\n\n\nGonzalo Gomez-Nogales, Melania Prieto-Martin, Cristian Romer
 o, Marc Comino-Trinidad, and Pablo Ramon-Prieto (Universidad Rey Juan Carl
 os); Anne-Hélène Olivier (INRIA, Université de Rennes, CNRS, IRISA,  M2S C
 entre de Rennes); Ludovic Hoyet (Institut national de recherche en informa
 tique et en automatique (INRIA)); Miguel Otaduy (Universidad Rey Juan Carl
 os); Julien Pettre (Institut national de recherche en informatique et en a
 utomatique (INRIA)); and Dan Casas (Universidad Rey Juan Carlos)\n--------
 -------------\nBody Gesture Generation for Multimodal Conversational Agent
 s\n\nCreating intelligent virtual agents with realistic conversational abi
 lities necessitates a multimodal communication approach extending beyond t
 ext. Body gestures, in particular, play a pivotal role in delivering a lif
 elike user experience by providing additional context, such as agreement, 
 confusion...\n\n\nSunwoo Kim, Minwook Chang, and Yoonhee Kim (NCSOFT) and 
 Jehee Lee (Seoul National University)\n\nRegistration Category: Full Acces
 s, Full Access Supporter\n\nLanguage Format: English Language\n\nSession C
 hair: Yi Zhou (Roblox)
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