Presentation / Installation


Neural Progressive Meshes
SessionDeep Geometric Learning
DescriptionDetailed high-resolution assets can pose a challenge to storage as well as transmission bandwidth. We propose a framework that learns a progressive compressed representation of meshes. Our framework progressively transmits data, allowing the client to control the tradeoff between bandwidth cost and quality of reconstruction.
Authors
Yun-Chun Chen
University of Toronto
Vladimir Kim
Adobe Research
Noam Aigerman
Adobe Research
Alec Jacobson
University of Toronto
Adobe Research
Event Type
Technical Paper
TimeThursday, 10 August 20232:53pm - 3:03pm PDT
LocationRoom 515 A
ACM Digital Library Technical Paper PDF
Session Time & Location
Sunday, 6 August 20236pm - 8:30pm PDTWest Hall B
Thursday, 10 August 20232pm - 3:30pm PDTRoom 515 A
Interest Areas
Research & Education
Recordings
Livestreamed
Recorded
Keywords
Modeling
Rendering
Registration Categories
FC
FCS
V
VS
EFC
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