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DTSTART:18871231T000000
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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_261@linklings.com
SUMMARY:MoRig: Motion-Aware Rigging of Character Meshes from Point Clouds
DESCRIPTION:Technical Communications, Technical Papers\n\nMoRig: Motion-Aw
 are Rigging of Character Meshes from Point Clouds\n\nXu, Zhou, Yi, Kaloger
 akis\n\nWe present MoRig, a method that automatically rigs character meshe
 s driven by single-view point cloud streams capturing the motion of perfor
 ming characters. Our method is also able to animate the 3D meshes accordin
 g to the captured point cloud motion. At the heart of our approach lies a 
 deep neural network that encodes motion cues from the point clouds into fe
 atures that are informative about the articulated parts of the performing 
 character. These features guide the inference of an appropriate skeletal r
 ig for the input mesh, which is then animated based on the input point clo
 ud motion. Our method can rig and animate diverse characters, including hu
 manoids, quadrupeds, and toys with varying articulations. It is designed t
 o account for occluded regions in the input point cloud sequences and any 
 mismatches in the part proportions between the input mesh and captured cha
 racter. Compared to other rigging approaches that ignore motion cues, our 
 method produces more accurate skeletal rigs, which are also more appropria
 te for re-targeting motion from captured characters.\n\nRegistration Categ
 ory: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: IN-PERS
 ON, ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_261&sess=sess15
 4
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