BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:Australia/Melbourne X-LIC-LOCATION:Australia/Melbourne BEGIN:DAYLIGHT TZOFFSETFROM:+1000 TZOFFSETTO:+1100 TZNAME:AEDT DTSTART:19721003T020000 RRULE:FREQ=YEARLY;BYMONTH=4;BYDAY=1SU END:DAYLIGHT BEGIN:STANDARD DTSTART:19721003T020000 TZOFFSETFROM:+1100 TZOFFSETTO:+1000 TZNAME:AEST RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240214T070246Z LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre) DTSTART;TZID=Australia/Melbourne:20231214T094000 DTEND;TZID=Australia/Melbourne:20231214T095000 UID:siggraphasia_SIGGRAPH Asia 2023_sess165_papers_712@linklings.com SUMMARY:Pose and Skeleton-aware Neural IK for Pose and Motion Editing DESCRIPTION:Technical Papers, TOG\n\nDhruv Agrawal (ETH Zürich, DisneyRese arch|Studios); Martin Guay, Jakob Buhmann, and Dominik Borer (DisneyResear ch|Studios); and Robert W. Sumner (DisneyResearch|Studios, ETH Zürich)\n\n Posing a 3D character for film or game is an iterative and laborious proce ss where many control handles (e.g. joints) need to be manipulated to achi eve a compelling result. Neural Inverse Kinematics (IK) is a new type of IK that enables sparse control over a 3D character pose, and leverages ful l body correlations to complete the un-manipulated joints of the body. Wh ile neural IK is promising, current methods are not designed to preserve p revious edits in posing workflows. Current models generate a full pose fro m the handles only---regardless of what was there previously---making it d ifficult to preserve any variations and hindering tasks such as pose and m otion editing.\n\nIn this paper, we introduce SKEL-IK, a novel architectur e and training scheme that is conditioned on a base pose, and designed to flow information directly onto the skeletal graph structure, such that har d constraints can be enforced by blocking information flows at certain joi nts. As a result, we are able to satisfy both hard and soft constraints, a s well as preserve un-manipulated parts of the body when desired. Finally, by controlling the base pose in different ways, we demonstrate the abilit y of our model to perform tasks such as generating variations and quickly editing poses and motions; with less erosion of the base poses compared to the current state-of-the-art.\n\nRegistration Category: Full Access URL:https://asia.siggraph.org/2023/full-program?id=papers_712&sess=sess165 END:VEVENT END:VCALENDAR