D-Index & Metrics Best Publications

Michael Goesele

Technical University of Darmstadt
Germany

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 31 Citations 5,862 150 World Ranking 9635 National Ranking 463

Overview

What is he best known for?

The fields of study Michael Goesele is best known for:

Computer graphics (images)
Computer animation
Texture mapping

His study explores the link between Cartography and topics such as Scale (ratio) that cross with problems in Quantum mechanics. His research on Quantum mechanics frequently connects to adjacent areas such as Scale (ratio). His Programming language study typically links adjacent topics like Set (abstract data type), Construct (python library) and Preprocessor. His work in Set (abstract data type) is not limited to one particular discipline; it also encompasses Programming language. He connects Artificial intelligence with Algorithm in his study. He integrates Algorithm and Database in his studies. With his scientific publications, his incorporates both Database and Scalability. He performs integrative study on Computer graphics (images) and Texture mapping. His research on Computer vision often connects related topics like Motion blur.

His most cited work include:

Image-based reconstruction of spatial appearance and geometric detail (291 citations)
Let There Be Color! Large-Scale Texturing of 3D Reconstructions (172 citations)
Floating scale surface reconstruction (145 citations)

What are the main themes of his work throughout his whole career to date

Michael Goesele is researching Rendering (computer graphics) as part of the investigation of Real-time rendering and Image-based modeling and rendering. His study deals with a combination of Real-time rendering and Rendering (computer graphics). Michael Goesele integrates Artificial intelligence with Data mining in his research. He incorporates Data mining and Artificial intelligence in his research. His study ties his expertise on Image (mathematics) together with the subject of Computer vision. His study connects Computer vision and Image (mathematics). While working on this project, he studies both Computer graphics (images) and Algorithm. He conducted interdisciplinary study in his works that combined Algorithm and Computer graphics (images). His Programming language study frequently intersects with other fields, such as Set (abstract data type).

Michael Goesele most often published in these fields:

Artificial intelligence (86.96%)
Computer vision (65.22%)
Computer graphics (images) (52.17%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Multi-View Stereo for Community Photo Collections

M. Goesele;N. Snavely;B. Curless;H. Hoppe.
international conference on computer vision (2007)

803 Citations

Multi-View Stereo Revisited

M. Goesele;B. Curless;S.M. Seitz.
computer vision and pattern recognition (2006)

423 Citations

Image-based reconstruction of spatial appearance and geometric detail

Hendrik P. A. Lensch;Jan Kautz;Michael Goesele;Wolfgang Heidrich.
ACM Transactions on Graphics (2003)

407 Citations

Let There Be Color! Large-Scale Texturing of 3D Reconstructions

Michael Waechter;Nils Moehrle;Michael Goesele.
european conference on computer vision (2014)

255 Citations

MVE: a multi-view reconstruction environment

Simon Fuhrmann;Fabian Langguth;Michael Goesele.
eurographics (2014)

240 Citations

Image-based reconstruction of spatially varying materials

Hendrik P. A. Lensch;Jan Kautz;Michael Goesele;Wolfgang Heidrich.
eurographics (2001)

210 Citations

Scene Reconstruction and Visualization From Community Photo Collections

Noah Snavely;Ian Simon;Michael Goesele;Richard Szeliski.
Proceedings of the IEEE (2010)

189 Citations

DISCO: acquisition of translucent objects

Michael Goesele;Hendrik P. A. Lensch;Jochen Lang;Christian Fuchs.
international conference on computer graphics and interactive techniques (2004)

188 Citations

Back to the Future: Learning Shape Models from 3D CAD Data

Michael Stark;Michael Goesele;Bernt Schiele.
british machine vision conference (2010)

185 Citations

The Replica Dataset: A Digital Replica of Indoor Spaces.

Julian Straub;Thomas Whelan;Lingni Ma;Yufan Chen.
arXiv: Computer Vision and Pattern Recognition (2019)

172 Citations

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Frequent Co-Authors

External Links

Personal Website for Michael Goesele