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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035307Z
LOCATION:Room 324\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T140000
DTEND;TZID=Asia/Seoul:20221206T153000
UID:siggraphasia_SIGGRAPH Asia 2022_sess154_papers_366@linklings.com
SUMMARY:Learning Virtual Chimeras by Dynamic Motion Reassembly
DESCRIPTION:Technical Communications, Technical Papers\n\nLearning Virtual
  Chimeras by Dynamic Motion Reassembly\n\nLEE, Lee, Lee\n\nThe Chimera is 
 a mythological hybrid creature composed of different animal parts. The chi
 mera’s movements are highly dependent on the spatial and temporal alignmen
 ts of its composing parts. In this paper, we present a novel algorithm tha
 t creates and animates chimeras by dynamically reassembling source charact
 ers and their movements. Our algorithm exploits a two-network architecture
 : part assembler and dynamic controller. The part assembler is a supervise
 d learning layer that searches for the spatial alignment among body parts,
  assuming that the temporal alignment is provided. The dynamic controller 
 is a reinforcement learning layer that learns robust control policy for a 
 wide variety of potential temporal alignments. These two layers are tightl
 y intertwined and learned simultaneously. The chimera animation generated 
 by our algorithm is energy efficient and expressive in terms of describing
  weight shifting, balancing, and full-body coordination. We demonstrate th
 e versatility of our algorithm by generating the motor skills of a large v
 ariety of chimeras from limited source characters.\n\nRegistration Categor
 y: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON
 , ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_366&sess=sess15
 4
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