H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 134 Citations 131,440 954 World Ranking 25 National Ranking 1

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Object detection and Segmentation. His research combines Machine learning and Artificial intelligence. His Computer vision study which covers Convolutional neural network that intersects with Deep learning, Artificial neural network and Pattern recognition.

His study in the fields of Discriminative model under the domain of Pattern recognition overlaps with other disciplines such as Regression. His studies in Object detection integrate themes in fields like Viola–Jones object detection framework, Detector, Object-class detection, Pascal and Pedestrian detection. His Segmentation research includes elements of Cluster analysis and Benchmark.

His most cited work include:

  • SURF: speeded up robust features (10422 citations)
  • Speeded-Up Robust Features (SURF) (9255 citations)
  • The Pascal Visual Object Classes (VOC) Challenge (8707 citations)

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

Luc Van Gool mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Image. The study of Artificial intelligence is intertwined with the study of Machine learning in a number of ways. His Computer vision research focuses on Tracking, 3D reconstruction, Video tracking, Motion and Pose.

He has included themes like Pascal and Feature in his Pattern recognition study. His research in Segmentation is mostly concerned with Image segmentation.

He most often published in these fields:

  • Artificial intelligence (80.52%)
  • Computer vision (47.38%)
  • Pattern recognition (23.98%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (80.52%)
  • Computer vision (47.38%)
  • Segmentation (12.79%)

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

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Segmentation, Pattern recognition and Image. The study incorporates disciplines such as Machine learning and Code in addition to Artificial intelligence. His Computer vision research includes themes of Process and Leverage.

His research integrates issues of Optical flow, Semantics, Synthetic data and Adaptation in his study of Segmentation. His Pattern recognition research integrates issues from Contextual image classification, Feature and Benchmark. His Image study combines topics in areas such as Domain, Set, Key, Translation and Generative grammar.

Between 2018 and 2021, his most popular works were:

  • Learning Discriminative Model Prediction for Tracking (172 citations)
  • Temporal Segment Networks for Action Recognition in Videos (151 citations)
  • Generative Adversarial Networks for Extreme Learned Image Compression (136 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

Luc Van Gool focuses on Artificial intelligence, Computer vision, Segmentation, Artificial neural network and Pattern recognition. His biological study spans a wide range of topics, including Algorithm, Machine learning and Code. His research links Leverage with Computer vision.

His Segmentation research is multidisciplinary, relying on both Domain, Natural language processing, Object, Benchmark and Synthetic data. His Artificial neural network research is multidisciplinary, incorporating elements of Network architecture, Set, Multi-task learning, Feature extraction and Convolutional neural network. His Pattern recognition research integrates issues from Object detection, Real image and Categorization.

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

SURF: speeded up robust features

Herbert Bay;Tinne Tuytelaars;Luc Van Gool.
european conference on computer vision (2006)

17942 Citations

Speeded-Up Robust Features (SURF)

Herbert Bay;Andreas Ess;Tinne Tuytelaars;Luc Van Gool.
Computer Vision and Image Understanding (2008)

12279 Citations

The Pascal Visual Object Classes (VOC) Challenge

Mark Everingham;Luc Gool;Christopher K. Williams;John Winn.
International Journal of Computer Vision (2010)

9180 Citations

The Pascal Visual Object Classes Challenge: A Retrospective

Mark Everingham;S. M. Eslami;Luc Gool;Christopher K. Williams.
International Journal of Computer Vision (2015)

2703 Citations

An adaptive color-based particle filter

Katja Nummiaro;Esther Koller-Meier;Luc J. Van Gool;Luc J. Van Gool.
Image and Vision Computing (2003)

1667 Citations

Self-Calibration and Metric Reconstruction Inspite of Varying and Unknown Intrinsic Camera Parameters

Marc Pollefeys;Reinhard Koch;Luc Van Gool.
International Journal of Computer Vision (1999)

1508 Citations

Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao.
european conference on computer vision (2016)

1376 Citations

Procedural modeling of buildings

Pascal Müller;Peter Wonka;Simon Haegler;Andreas Ulmer.
international conference on computer graphics and interactive techniques (2006)

1321 Citations

Visual Modeling with a Hand-Held Camera

Marc Pollefeys;Luc Van Gool;Maarten Vergauwen;Frank Verbiest.
International Journal of Computer Vision (2004)

1254 Citations

A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution

Radu Timofte;Vincent De Smet;Luc J. Van Gool;Luc J. Van Gool.
asian conference on computer vision (2014)

1186 Citations

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Best Scientists Citing Luc Van Gool

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 182

Marc Pollefeys

Marc Pollefeys

ETH Zurich

Publications: 167

Andrew Zisserman

Andrew Zisserman

University of Oxford

Publications: 157

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 134

Chunhua Shen

Chunhua Shen

University of Adelaide

Publications: 122

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

Publications: 119

Bernt Schiele

Bernt Schiele

Max Planck Institute for Informatics

Publications: 109

Shuicheng Yan

Shuicheng Yan

National University of Singapore

Publications: 108

Philip H. S. Torr

Philip H. S. Torr

University of Oxford

Publications: 103

Nicu Sebe

Nicu Sebe

University of Trento

Publications: 103

Vittorio Ferrari

Vittorio Ferrari

Google (United States)

Publications: 100

Cordelia Schmid

Cordelia Schmid

French Institute for Research in Computer Science and Automation - INRIA

Publications: 100

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 100

Tinne Tuytelaars

Tinne Tuytelaars

KU Leuven

Publications: 96

Larry S. Davis

Larry S. Davis

University of Maryland, College Park

Publications: 95

Horst Bischof

Horst Bischof

Graz University of Technology

Publications: 95

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