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SUMMARY:SIG Seminar: "Uncertainty-Driven Geometry Reconstruction and Understanding"
DESCRIPTION:Choosing suitable data representations is one of the most critical topics when installing machine learning on 3D data. This talk discusses several recent works on utilizing uncertainty as a lens to develop suitable data representations and formulations for geometry reconstruction and understanding. We will discuss both theoretical results and applications in multi-scan registration\, pose estimation\, and scene understanding.
URL:https://seasevents.nmsdev7.com/event/sig-seminar-uncertainty-driven-geometry-reconstruction-and-understanding/
LOCATION:Zoom – Email CIS for link\, cherylh@cis.upenn.edu
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
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