H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 95 Citations 35,302 466 World Ranking 192 National Ranking 10

Research.com Recognitions

Awards & Achievements

2012 - ACM Fellow For contributions to computer graphics and animation.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Computer graphics

His primary areas of investigation include Artificial intelligence, Computer vision, Computer graphics, Algorithm and Rendering. His Artificial intelligence study incorporates themes from Set and Pattern recognition. His work in the fields of Pixel, Structured light, Motion capture and Facial geometry overlaps with other areas such as Volume.

His Computer graphics research includes elements of Image warping, Stereoscopy and Visual artifact. His research integrates issues of Point cloud, Moving least squares, Mesh generation, Surface and Mathematical optimization in his study of Algorithm. As part of the same scientific family, Markus Gross usually focuses on Rendering, concentrating on Texture mapping and intersecting with Texture filtering and Surfel.

His most cited work include:

  • Particle-based fluid simulation for interactive applications (842 citations)
  • A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation (806 citations)
  • Surfels: surface elements as rendering primitives (709 citations)

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

Markus Gross mostly deals with Artificial intelligence, Computer vision, Computer graphics, Rendering and Algorithm. Markus Gross combines subjects such as Machine learning, Process and Pattern recognition with his study of Artificial intelligence. His study in Pixel, Stereoscopy, Video processing, Object and Image processing falls under the purview of Computer vision.

His research on Computer graphics frequently links to adjacent areas such as Image warping. His study in Rendering is interdisciplinary in nature, drawing from both Graphics pipeline and Graphics. His Algorithm research incorporates themes from Surface and Wavelet.

He most often published in these fields:

  • Artificial intelligence (52.77%)
  • Computer vision (42.95%)
  • Computer graphics (28.84%)

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

  • Artificial intelligence (52.77%)
  • Computer vision (42.95%)
  • Visualization (8.72%)

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

Markus Gross mainly focuses on Artificial intelligence, Computer vision, Visualization, Artificial neural network and Algorithm. His Artificial intelligence study integrates concerns from other disciplines, such as Natural language processing, Machine learning and Pattern recognition. The concepts of his Computer vision study are interwoven with issues in Frame and Computer graphics.

His Visualization study combines topics in areas such as Multimedia and Human–computer interaction. His Artificial neural network research is multidisciplinary, incorporating perspectives in Segmentation and Feature extraction. His Algorithm study combines topics from a wide range of disciplines, such as Vector field, Theoretical computer science, Divergence and Rendering.

Between 2016 and 2021, his most popular works were:

  • Towards better understanding of gradient-based attribution methods for Deep Neural Networks (285 citations)
  • Deep Fluids: A Generative Network for Parameterized Fluid Simulations (97 citations)
  • A unified view of gradient-based attribution methods for Deep Neural Networks (75 citations)

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

  • Artificial intelligence
  • Computer vision
  • Computer graphics

Markus Gross spends much of his time researching Artificial intelligence, Artificial neural network, Computer vision, Algorithm and Deep learning. The study incorporates disciplines such as Network architecture and Machine learning in addition to Artificial intelligence. His studies deal with areas such as Computer graphics and State as well as Computer vision.

His Computer animation and Computer facial animation study in the realm of Computer graphics interacts with subjects such as Facial motion capture and Facial tissue. His work carried out in the field of Algorithm brings together such families of science as Memory footprint, Divergence, Computer graphics and Rendering. The Deep learning study which covers Interpolation that intersects with Solver, Motion blur, Frame and Motion interpolation.

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

Particle-based fluid simulation for interactive applications

Matthias Müller;David Charypar;Markus Gross.
symposium on computer animation (2003)

1691 Citations

Surfels: surface elements as rendering primitives

Hanspeter Pfister;Matthias Zwicker;Jeroen van Baar;Markus Gross.
international conference on computer graphics and interactive techniques (2000)

1214 Citations

Efficient simplification of point-sampled surfaces

Mark Pauly;Markus Gross;Leif P. Kobbelt.
ieee visualization (2002)

1183 Citations

Surface splatting

Matthias Zwicker;Hanspeter Pfister;Jeroen van Baar;Markus Gross.
international conference on computer graphics and interactive techniques (2001)

804 Citations

Meshless deformations based on shape matching

Matthias Müller;Bruno Heidelberger;Matthias Teschner;Markus Gross.
international conference on computer graphics and interactive techniques (2005)

677 Citations

Shape modeling with point-sampled geometry

Mark Pauly;Richard Keiser;Leif P. Kobbelt;Markus Gross.
international conference on computer graphics and interactive techniques (2003)

646 Citations

A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation

F. Perazzi;J. Pont-Tuset;B. McWilliams;L. Van Gool.
computer vision and pattern recognition (2016)

642 Citations

Optimized Spatial Hashing for Collision Detection of Deformable Objects.

Matthias Teschner;Bruno Heidelberger;Matthias Müller;Danat Pomerantes.
vision modeling and visualization (2003)

624 Citations

Interactive virtual materials

Matthias Müller;Markus Gross.
graphics interface (2004)

615 Citations

Multi-scale Feature Extraction on Point-Sampled Surfaces

Mark Pauly;Richard Keiser;Markus H. Gross.
Computer Graphics Forum (2003)

605 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Markus Gross

Hans-Peter Seidel

Hans-Peter Seidel

Max Planck Institute for Informatics

Publications: 131

Christian Theobalt

Christian Theobalt

Max Planck Institute for Informatics

Publications: 84

Hong Qin

Hong Qin

Stony Brook University

Publications: 66

Kun Zhou

Kun Zhou

Zhejiang University

Publications: 63

Wojciech Matusik

Wojciech Matusik

MIT

Publications: 59

Niloy J. Mitra

Niloy J. Mitra

University College London

Publications: 58

Matthias Teschner

Matthias Teschner

University of Freiburg

Publications: 58

Thomas Ertl

Thomas Ertl

University of Stuttgart

Publications: 57

Dinesh Manocha

Dinesh Manocha

University of Maryland, College Park

Publications: 56

Daniel Cohen-Or

Daniel Cohen-Or

Tel Aviv University

Publications: 53

Ming C. Lin

Ming C. Lin

University of Maryland, College Park

Publications: 51

Ronald Fedkiw

Ronald Fedkiw

Stanford University

Publications: 48

Hao Li

Hao Li

University of California, Berkeley

Publications: 47

Shi-Min Hu

Shi-Min Hu

Tsinghua University

Publications: 46

Marcus Magnor

Marcus Magnor

Technische Universität Braunschweig

Publications: 43

Bernd Hamann

Bernd Hamann

University of California, Davis

Publications: 43

Something went wrong. Please try again later.