H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 30 Citations 5,706 113 World Ranking 8883 National Ranking 422

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Computer graphics

Michael Goesele mainly investigates Artificial intelligence, Computer vision, Computer graphics, Rendering and Iterative reconstruction. His work on Object as part of general Artificial intelligence research is often related to Knowledge transfer, thus linking different fields of science. The study incorporates disciplines such as Polygon mesh and Surface reconstruction in addition to Computer vision.

The study incorporates disciplines such as Visualization, Data visualization, Viewpoints and The Internet in addition to Computer graphics. His work in Rendering addresses issues such as Bidirectional reflectance distribution function, which are connected to fields such as Point light source and Global illumination. His Iterative reconstruction research is multidisciplinary, relying on both Computer stereo vision, Stereopsis, Reflectivity, Algorithm design and Robustness.

His most cited work include:

  • Multi-View Stereo for Community Photo Collections (544 citations)
  • Image-based reconstruction of spatial appearance and geometric detail (272 citations)
  • Multi-View Stereo Revisited (254 citations)

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

His primary areas of investigation include Artificial intelligence, Computer vision, Computer graphics, Rendering and Algorithm. His Artificial intelligence research integrates issues from Pattern recognition and Surface reconstruction. His study in Computer vision is interdisciplinary in nature, drawing from both Polygon mesh and Surface.

His Computer graphics research includes themes of Visualization and Point cloud. His Rendering study frequently draws connections to other fields, such as Bidirectional reflectance distribution function. His Photometric stereo study incorporates themes from Stereo camera and Normal mapping.

He most often published in these fields:

  • Artificial intelligence (46.63%)
  • Computer vision (38.04%)
  • Computer graphics (29.45%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (46.63%)
  • Computer vision (38.04%)
  • Pattern recognition (5.52%)

In recent papers he was focusing on the following fields of study:

Michael Goesele mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Deep learning and Convolutional neural network. His Artificial intelligence study combines topics from a wide range of disciplines, such as Focus and Replica. His Computer vision research incorporates themes from Representation and Point.

His studies deal with areas such as Video tracking, Object, Background subtraction and Segmentation as well as Deep learning. The Convolutional neural network study combines topics in areas such as Pooling and Leverage. His research investigates the connection between 3D reconstruction and topics such as Haptic technology that intersect with issues in Computer graphics.

Between 2016 and 2021, his most popular works were:

  • The Replica Dataset: A Digital Replica of Indoor Spaces. (74 citations)
  • Detail-Preserving Pooling in Deep Networks (32 citations)
  • Virtual Rephotography: Novel View Prediction Error for 3D Reconstruction (24 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Algorithm

Michael Goesele focuses on Artificial intelligence, Computer vision, Deep learning, Pattern recognition and Algorithm. His Artificial intelligence research focuses on Rendering in particular. His 3d scanning study in the realm of Computer vision interacts with subjects such as Pipeline.

His studies in Deep learning integrate themes in fields like Segmentation, Pooling, Leverage, Video tracking and Convolutional neural network. His work deals with themes such as Object, Perspective and Background subtraction, which intersect with Pattern recognition. His research integrates issues of Kernel and Surface reconstruction in his study of Algorithm.

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.

Top Publications

Multi-View Stereo for Community Photo Collections

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

765 Citations

Multi-View Stereo Revisited

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

405 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)

377 Citations

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

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

246 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)

204 Citations

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

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

184 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)

184 Citations

Scene Reconstruction and Visualization From Community Photo Collections

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

181 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)

171 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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