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A super-resolution framework for high-accuracy multiview reconstruction

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Publication:903440
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DOI10.1007/s11263-013-0654-8zbMath1328.68239OpenAlexW1970260218MaRDI QIDQ903440

Daniel Cremers, Mathieu Aubry, Bastian Goldlücke, Kalin Kolev

Publication date: 6 January 2016

Published in: International Journal of Computer Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11263-013-0654-8


zbMATH Keywords

variational methodscamera calibrationsuper-resolutionmulti-view 3D reconstructiontexture reconstruction


Mathematics Subject Classification ID

Machine vision and scene understanding (68T45)


Related Items

Efficient convex optimization-based texture mapping for large-scale 3D scene reconstruction ⋮ Shading-based refinement on volumetric signed distance functions



Cites Work

  • Nonlinear total variation based noise removal algorithms
  • A first-order primal-dual algorithm for convex problems with applications to imaging
  • The Natural Vectorial Total Variation Which Arises from Geometric Measure Theory
  • Variational Analysis in Sobolev andBVSpaces
  • A Silhouette-Based Algorithm for Texture Registration and Stitching
  • Multiple View Geometry in Computer Vision
  • A Coding-Cost Framework for Super-Resolution Motion Layer Decomposition
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