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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) S. 5470 - 5480
1. Verfasser:	Kaneko, Takuhiro
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 16.06.2024
Schlagworte:	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
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!