H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 58 Citations 13,557 157 World Ranking 1802 National Ranking 77

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Juergen Gall mostly deals with Artificial intelligence, Computer vision, Pose, Pattern recognition and 3D pose estimation. His Artificial intelligence research focuses on subjects like Machine learning, which are linked to Image segmentation. His work on Motion capture as part of general Computer vision research is often related to Regression, thus linking different fields of science.

His biological study deals with issues like Hough transform, which deal with fields such as Codebook, Implicit Shape Model, Object and Video tracking. Within one scientific family, Juergen Gall focuses on topics pertaining to Robustness under 3D pose estimation, and may sometimes address concerns connected to Facial recognition system, Facial expression, Graphics, Ground truth and Optical flow estimation. His Object detection research includes themes of Categorization and Contrast.

His most cited work include:

  • Towards Understanding Action Recognition (529 citations)
  • Hough Forests for Object Detection, Tracking, and Action Recognition (491 citations)
  • Class-specific Hough forests for object detection (431 citations)

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

Juergen Gall mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Pose. His study in Segmentation, Object, Image, Object detection and Convolutional neural network is carried out as part of his Artificial intelligence studies. His Computer vision study deals with Benchmark intersecting with Representation.

His research integrates issues of Supervised learning, Random forest, Hough transform and Inference in his study of Pattern recognition. His biological study spans a wide range of topics, including Visualization, Data mining, Hidden Markov model and Set. As part of the same scientific family, Juergen Gall usually focuses on Pose, concentrating on Training set and intersecting with Field.

He most often published in these fields:

  • Artificial intelligence (91.15%)
  • Computer vision (41.15%)
  • Pattern recognition (30.09%)

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

  • Artificial intelligence (91.15%)
  • Segmentation (18.14%)
  • Machine learning (26.99%)

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

The scientist’s investigation covers issues in Artificial intelligence, Segmentation, Machine learning, Pattern recognition and Computer vision. His study in Set extends to Artificial intelligence with its themes. His Segmentation research also works with subjects such as

  • Hidden Markov model that connect with fields like Supervised learning,
  • Point cloud that connect with fields like Projection,
  • Noise together with Benchmark.

His studies in Pattern recognition integrate themes in fields like Image quality, Ground truth, Real image and Transformer. His study in Computer vision is interdisciplinary in nature, drawing from both Memorization and Overfitting. His work is dedicated to discovering how Pose, Motion blur are connected with Tracking and other disciplines.

Between 2019 and 2021, his most popular works were:

  • Open Set Domain Adaptation for Image and Action Recognition (25 citations)
  • A Hybrid RNN-HMM Approach for Weakly Supervised Temporal Action Segmentation (19 citations)
  • MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation. (10 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

His scientific interests lie mostly in Artificial intelligence, Segmentation, Hidden Markov model, Pattern recognition and Deep learning. He combines subjects such as Data mining and Computer vision with his study of Artificial intelligence. In general Computer vision study, his work on Pose tracking, Pose and Tracking often relates to the realm of Scale, thereby connecting several areas of interest.

His work deals with themes such as Point cloud, Field and Projection, which intersect with Segmentation. His Hidden Markov model research focuses on Supervised learning and how it relates to Transformer and Set. The various areas that Juergen Gall examines in his Pattern recognition study include Ground truth, Real image and Noise.

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

Hough Forests for Object Detection, Tracking, and Action Recognition

J. Gall;A. Yao;N. Razavi;L. Van Gool.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2011)

648 Citations

Class-specific Hough forests for object detection

Juergen Gall;Victor Lempitsky.
computer vision and pattern recognition (2009)

580 Citations

Real time head pose estimation with random regression forests

Gabriele Fanelli;Juergen Gall;Luc Van Gool.
computer vision and pattern recognition (2011)

503 Citations

Towards Understanding Action Recognition

Hueihan Jhuang;Juergen Gall;Silvia Zuffi;Cordelia Schmid.
international conference on computer vision (2013)

464 Citations

Real-time facial feature detection using conditional regression forests

Matthias Dantone;Juergen Gall;Gabriele Fanelli;Luc Van Gool.
computer vision and pattern recognition (2012)

460 Citations

Motion capture using joint skeleton tracking and surface estimation

Juergen Gall;Carsten Stoll;Edilson de Aguiar;Christian Theobalt.
computer vision and pattern recognition (2009)

419 Citations

Random Forests for Real Time 3D Face Analysis

Gabriele Fanelli;Matthias Dantone;Juergen Gall;Andrea Fossati.
International Journal of Computer Vision (2013)

393 Citations

Real time head pose estimation from consumer depth cameras

Gabriele Fanelli;Thibaut Weise;Juergen Gall;Luc Van Gool.
international conference on pattern recognition (2011)

360 Citations

A Hough transform-based voting framework for action recognition

Angela Yao;Juergen Gall;Luc Van Gool.
computer vision and pattern recognition (2010)

334 Citations

Optimization and Filtering for Human Motion Capture

Juergen Gall;Bodo Rosenhahn;Thomas Brox;Hans-Peter Seidel.
International Journal of Computer Vision (2010)

282 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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