Sat-Mesh: Learning Neural Implicit Surfaces for Multi-View Satellite Reconstruction

Automatic reconstruction of surfaces from satellite imagery is a hot topic in computer vision and photogrammetry. State-of-the-art reconstruction methods typically produce 2.5D elevation data. In contrast, we propose a one-stage method directly generating a 3D mesh model from multi-view satellite im...

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Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Vol. 15; no. 17; p. 4297
Main Authors:	Qu, Yingjie, Deng, Fei
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.08.2023
Subjects:	Accuracy Artificial intelligence Cameras Comparative analysis Computer architecture Computer vision Continuity (mathematics) Efficiency Finite element method Geometry Image enhancement Image reconstruction latent appearance Learning Machine learning Mesh generation Methods neural implicit surfaces Neural networks neural radiance fields normalized cross-correlation Orientation behavior Photogrammetry Production methods Remote sensing satellite 3D reconstruction Satellite imagery Satellite imaging satellites Seasonal variations Surface properties surface quality Technology application texture Three dimensional models China
ISSN:	2072-4292, 2072-4292
Online Access:	Get full text
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