H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 38 Citations 7,250 72 World Ranking 5133 National Ranking 230

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Gerard Pons-Moll spends much of his time researching Artificial intelligence, Computer vision, Pose, Motion capture and Motion. Gerard Pons-Moll brings together Artificial intelligence and Clothing to produce work in his papers. His studies examine the connections between Computer vision and genetics, as well as such issues in Animation, with regards to Visual hull and Silhouette.

Gerard Pons-Moll combines topics linked to Computer graphics with his work on Motion. His RGB color model research is multidisciplinary, incorporating perspectives in Face and Gesture. His Solid modeling study combines topics from a wide range of disciplines, such as Representation, Parameterized complexity, Deep learning, Iterative reconstruction and Pattern recognition.

His most cited work include:

  • SMPL: a skinned multi-person linear model (896 citations)
  • Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation (260 citations)
  • Dyna: a model of dynamic human shape in motion (231 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, Pose, Motion capture and Polygon mesh. Gerard Pons-Moll merges many fields, such as Artificial intelligence and Clothing, in his writings. The study incorporates disciplines such as Artificial neural network and Representation in addition to Computer vision.

His studies in Pose integrate themes in fields like Perspective and Machine learning, Convolutional neural network, Pattern recognition. He focuses mostly in the field of Motion capture, narrowing it down to topics relating to Retargeting and, in certain cases, Single view. His work deals with themes such as Animation, Point cloud, Graphics, Algorithm and Rendering, which intersect with Polygon mesh.

He most often published in these fields:

  • Artificial intelligence (84.07%)
  • Computer vision (65.49%)
  • Pose (23.01%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (84.07%)
  • Computer vision (65.49%)
  • Algorithm (10.62%)

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

Gerard Pons-Moll mostly deals with Artificial intelligence, Computer vision, Algorithm, Polygon mesh and Code. He performs multidisciplinary study on Artificial intelligence and Clothing in his works. His Computer vision research includes themes of Range and Deep learning.

The concepts of his Algorithm study are interwoven with issues in Point cloud and Distance transform. His Polygon mesh study which covers Graphics that intersects with Shape approximation and 3d tracking. His Pose research is multidisciplinary, relying on both Ground truth, Tracking, Perspective and Motion capture.

Between 2019 and 2021, his most popular works were:

  • Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion (67 citations)
  • Learning to Dress 3D People in Generative Clothing (41 citations)
  • XNect: real-time multi-person 3D motion capture with a single RGB camera (38 citations)

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

  • Artificial intelligence
  • Computer vision
  • Algorithm

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Monocular, Implicit function and Polygon mesh. His Artificial intelligence study frequently links to related topics such as Contrast. In the field of Computer vision, his study on Rendering overlaps with subjects such as Radiance.

His Monocular research integrates issues from Pose and Motion capture. His research in Pose intersects with topics in RGB color model, Convolutional neural network and Range. His studies deal with areas such as Shape approximation and Representation as well as Polygon mesh.

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

SMPL: a skinned multi-person linear model

Matthew Loper;Naureen Mahmood;Javier Romero;Gerard Pons-Moll.
international conference on computer graphics and interactive techniques (2015)

727 Citations

ClothCap: seamless 4D clothing capture and retargeting

Gerard Pons-Moll;Sergi Pujades;Sonny Hu;Michael J. Black.
ACM Transactions on Graphics (2017)

322 Citations

Dyna: a model of dynamic human shape in motion

Gerard Pons-Moll;Javier Romero;Naureen Mahmood;Michael J. Black.
international conference on computer graphics and interactive techniques (2015)

274 Citations

Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation

Mohamed Omran;Christoph Lassner;Gerard Pons-Moll;Peter Gehler.
international conference on 3d vision (2018)

260 Citations

Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker

Laura Leal-Taixe;Gerard Pons-Moll;Bodo Rosenhahn.
international conference on computer vision (2011)

212 Citations

Recovering Accurate {3D} Human Pose in the Wild Using {IMUs} and a Moving Camera

Timo von Marcard;Roberto Henschel;Michael J. Black;Bodo Rosenhahn.
european conference on computer vision (2018)

203 Citations

Dynamic FAUST: Registering Human Bodies in Motion

Federica Bogo;Javier Romero;Gerard Pons-Moll;Michael J. Black.
computer vision and pattern recognition (2017)

198 Citations

AMASS: Archive of Motion Capture As Surface Shapes

Naureen Mahmood;Nima Ghorbani;Nikolaus F. Troje;Gerard Pons-Moll.
international conference on computer vision (2019)

171 Citations

Learning to Reconstruct People in Clothing From a Single RGB Camera

Thiemo Alldieck;Marcus Magnor;Bharat Lal Bhatnagar;Christian Theobalt.
computer vision and pattern recognition (2019)

171 Citations

Video Based Reconstruction of 3D People Models

Thiemo Alldieck;Marcus Magnor;Weipeng Xu;Christian Theobalt.
computer vision and pattern recognition (2018)

168 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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