D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 62 Citations 18,481 137 World Ranking 1384 National Ranking 796

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 Object. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning. His study in the field of Cognitive neuroscience of visual object recognition, Articulated body pose estimation, Pose and Pixel is also linked to topics like Object-class detection.

His Cognitive neuroscience of visual object recognition study integrates concerns from other disciplines, such as Video tracking and Pattern recognition. The Pattern recognition study combines topics in areas such as Image and Data mining. His work deals with themes such as Image sensor, Feature, Image processing, Contextual image classification and Supervised learning, which intersect with Object detection.

His most cited work include:

  • Measuring the Objectness of Image Windows (1066 citations)
  • ClassCut for unsupervised class segmentation (995 citations)
  • What is an object (771 citations)

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

His primary scientific interests are in Artificial intelligence, Computer vision, Object, Pattern recognition and Segmentation. His Machine learning research extends to Artificial intelligence, which is thematically connected. His work carried out in the field of Computer vision brings together such families of science as Detector and Pattern recognition.

The concepts of his Object study are interwoven with issues in Motion, Representation and Automatic image annotation. His biological study spans a wide range of topics, including Pixel and Algorithm. His studies in Object detection integrate themes in fields like Contextual image classification, Support vector machine and Image processing.

He most often published in these fields:

  • Artificial intelligence (81.43%)
  • Computer vision (38.10%)
  • Object (35.24%)

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

  • Artificial intelligence (81.43%)
  • Object (35.24%)
  • Computer vision (38.10%)

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

Artificial intelligence, Object, Computer vision, Segmentation and Image are his primary areas of study. His research integrates issues of Natural language processing, Machine learning and Pattern recognition in his study of Artificial intelligence. His Pattern recognition research is multidisciplinary, relying on both Domain, Adaptation and Test set.

His work in Object covers topics such as Pattern recognition which are related to areas like Human–computer interaction. Vittorio Ferrari works mostly in the field of Computer vision, limiting it down to concerns involving Representation and, occasionally, CAD. His Segmentation study combines topics in areas such as Pixel, Algorithm and Automatic image annotation.

Between 2018 and 2021, his most popular works were:

  • The Open Images Dataset V4: Unified Image Classification, Object Detection, and Visual Relationship Detection at Scale (154 citations)
  • Large-Scale Interactive Object Segmentation With Human Annotators (62 citations)
  • Learning Single-Image 3D Reconstruction by Generative Modelling of Shape, Pose and Shading (58 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, Object, Segmentation, Image and Pattern recognition. His research in Artificial intelligence intersects with topics in Machine learning and Computer vision. His study on Voxel, Automatic image annotation and Image segmentation is often connected to Focus and Space as part of broader study in Computer vision.

His Object study frequently intersects with other fields, such as Pattern recognition. In his work, Closed captioning and Word is strongly intertwined with Natural language processing, which is a subfield of Image. His research investigates the connection with Pattern recognition and areas like Representation which intersect with concerns in Pixel, Bilinear interpolation, Machine vision and Upsampling.

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

Measuring the Objectness of Image Windows

B. Alexe;T. Deselaers;V. Ferrari.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)

1399 Citations

What is an object

Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari.
computer vision and pattern recognition (2010)

1220 Citations

ClassCut for unsupervised class segmentation

Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari.
european conference on computer vision (2010)

997 Citations

Progressive search space reduction for human pose estimation

V. Ferrari;M. Marin-Jimenez;A. Zisserman.
computer vision and pattern recognition (2008)

862 Citations

Groups of Adjacent Contour Segments for Object Detection

V. Ferrari;L. Fevrier;F. Jurie;C. Schmid.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

697 Citations

Segmentation propagation in imagenet

Daniel Kuettel;Matthieu Guillaumin;Vittorio Ferrari.
european conference on computer vision (2012)

609 Citations

Fast Object Segmentation in Unconstrained Video

Anestis Papazoglou;Vittorio Ferrari.
international conference on computer vision (2013)

579 Citations

Learning Visual Attributes

Vittorio Ferrari;Andrew Zisserman.
neural information processing systems (2007)

516 Citations

Learning object class detectors from weakly annotated video

Alessandro Prest;Christian Leistner;Javier Civera;Cordelia Schmid.
computer vision and pattern recognition (2012)

473 Citations

What’s the Point: Semantic Segmentation with Point Supervision

Amy Bearman;Olga Russakovsky;Vittorio Ferrari;Li Fei-Fei.
european conference on computer vision (2016)

448 Citations

Best Scientists Citing Vittorio Ferrari

Luc Van Gool

Luc Van Gool

ETH Zurich

Publications: 97

Bernt Schiele

Bernt Schiele

Max Planck Institute for Informatics

Publications: 86

Andrew Zisserman

Andrew Zisserman

University of Oxford

Publications: 77

Kristen Grauman

Kristen Grauman

Facebook (United States)

Publications: 59

Alan L. Yuille

Alan L. Yuille

Johns Hopkins University

Publications: 57

Shuicheng Yan

Shuicheng Yan

National University of Singapore

Publications: 57

Cordelia Schmid

Cordelia Schmid

French Institute for Research in Computer Science and Automation - INRIA

Publications: 54

Li Fei-Fei

Li Fei-Fei

Stanford University

Publications: 52

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 51

Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

Publications: 48

Larry S. Davis

Larry S. Davis

University of Maryland, College Park

Publications: 45

Martial Hebert

Martial Hebert

Carnegie Mellon University

Publications: 41

Tao Xiang

Tao Xiang

University of Surrey

Publications: 41

Tinne Tuytelaars

Tinne Tuytelaars

KU Leuven

Publications: 41

Silvio Savarese

Silvio Savarese

Stanford University

Publications: 41

Liang Lin

Liang Lin

Sun Yat-sen University

Publications: 39

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

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