Presentation

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HQ3DAvatar: High Quality Implicit 3D Head Avatar
Session3D Head Avatars From Data
DescriptionWe present a novel method for rendering photorealistic human head avatars. Our method utilizes an implicitly learned canonical space constrained using optical flow in a multiresolution hash encoding framework. Our approach outperforms related methods and excels in reconstructing regions exhibiting complex geometric details e.g. mouth interior and hair.
Authors
Kartik Teotia
Max Planck Institute for Informatics
Byrasandra Ramalinga Reddy Mallikarjun
Max Planck Institute for Informatics
Xingang Pan
Max Planck Institute for Informatics
Nanyang Technological University
Hyeongwoo Kim
Imperial College London
Pablo Garrido
Flawless AI
Mohamed Elgharib
Max Planck Institute for Informatics
Christian Theobalt
Max Planck Institute for Informatics
Presenter
Kartik Teotia
Max Planck Institute for Informatics, Saarland Informatics Campus
Event Type
Technical Paper
TimeWednesday, 31 July 20249:00am - 9:10am MDT
LocationMile High 1
ACM Digital Library Journal Papers' PDFs
Conference Papers' PDFs
Session Time & Location
Sunday, 28 July 20246:00pm - 8:45pm MDTBluebird Ballroom
Wednesday, 31 July 20249:00am - 10:30am MDTMile High 1
Interest Areas
Research & Education
Recordings
Livestreamed
Recorded
Keywords
Animation
Geometry
Modeling
Rendering
Registration Categories
Full Conference
Full Conference Supporter
Virtual Access
Exhibitor Full Conference
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