Improving Physics-Augmented Continuum Neural Radiance Field-Based Geometry-Agnostic System Identification with Lagrangian Particle Optimization

Geometry-agnostic system identification is a technique for identifying the geometry and physical properties of an object from video sequences without any geometric as-sumptions. Recently, physics-augmented continuum neural radiance fields (PAC-NeRF) has demonstrated promising results for this techni...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 5470 - 5480
Hlavný autor:	Kaneko, Takuhiro
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 16.06.2024
Predmet:	Computational modeling Computer vision few-shot learning Geometry Lagrangian representation Neural radiance field neural radiance fields Pattern recognition physics-informed models System identification Video sequences
ISSN:	1063-6919
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