Presentation

Neural Bounding
DescriptionOur research introduces a neural approach to bounding volumes, conservatively classifying space across diverse dimensions and scenes. The key is a novel loss function that produces minimal false negatives. Our method extends to non-neural and hybrid representations. We also propose an early exit strategy that accelerates query speeds by 25%.
Event Type
Technical Paper
TimeThursday, 1 August 20249:20am - 9:30am MDT
LocationMile High 2A
Session Time & Location
Sunday, 28 July 20246:00pm - 8:45pm MDTBluebird Ballroom
Thursday, 1 August 20249:00am - 10:30am MDTMile High 2A
Interest Areas
Research & Education
Recordings
Livestreamed
Recorded
Keywords
Geometry
Modeling
Registration Categories
Full Conference
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Virtual Access
Exhibitor Full Conference
Thursday