H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 143 Citations 171,887 367 World Ranking 17 National Ranking 11

Research.com Recognitions

Awards & Achievements

2016 - ACM AAAI Allen Newell Award For seminal contributions in multiple aspects of computer vision, computer graphics, and computational models of human vision.

2015 - Member of the National Academy of Sciences

2014 - IAPR King-Sun Fu Prize For contributions to fundamental algorithms and their theoretical underpinnings in computer vision.

2013 - Fellow of the American Academy of Arts and Sciences

2011 - Member of the National Academy of Engineering For contributions to computer vision and image analysis.

2008 - ACM Fellow For contributions to computer vision.

2006 - IEEE Fellow For contributions to computer vision and image analysis.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Jitendra Malik mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Image segmentation. His studies in Object detection, Cognitive neuroscience of visual object recognition, Pixel, Feature and Pascal are all subfields of Artificial intelligence research. His research on Object detection also deals with topics like

  • Convolutional neural network that intertwine with fields like Object,
  • Detector and related Brightness and Edge detection.

The study incorporates disciplines such as Contextual image classification, Caltech 101 and Image retrieval in addition to Pattern recognition. His Segmentation research is multidisciplinary, incorporating perspectives in Ground truth, Point, Minimum bounding box and Salience. His Image segmentation research focuses on Graph theory and how it relates to Graph and Graph partition.

His most cited work include:

  • Normalized cuts and image segmentation (12494 citations)
  • Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation (12438 citations)
  • Scale-space and edge detection using anisotropic diffusion (10015 citations)

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

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Machine learning. Image segmentation, Object, Cognitive neuroscience of visual object recognition, Object detection and Image are subfields of Artificial intelligence in which his conducts study. His study in Pixel, Image texture, Stereopsis, Edge detection and Scale-space segmentation is carried out as part of his Computer vision studies.

His research links Feature with Pattern recognition. His Segmentation study integrates concerns from other disciplines, such as Ground truth and Point. His Machine learning study often links to related topics such as Set.

He most often published in these fields:

  • Artificial intelligence (80.04%)
  • Computer vision (46.84%)
  • Pattern recognition (27.27%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (80.04%)
  • Machine learning (13.64%)
  • Computer vision (46.84%)

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

Artificial intelligence, Machine learning, Computer vision, Object and Human–computer interaction are his primary areas of study. His research in Artificial intelligence intersects with topics in Set and Pattern recognition. His study in Pattern recognition is interdisciplinary in nature, drawing from both Structure and Image.

His Machine learning research incorporates elements of Generative grammar and Trajectory. His work deals with themes such as Representation, Polygon mesh, Benchmark and Key, which intersect with Computer vision. He combines subjects such as Optical flow, Feature extraction and Stereoscopy with his study of Object.

Between 2017 and 2021, his most popular works were:

  • End-to-End Recovery of Human Shape and Pose (660 citations)
  • SlowFast Networks for Video Recognition (480 citations)
  • Taskonomy: Disentangling Task Transfer Learning (385 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary areas of study are Artificial intelligence, Robot, Computer vision, Motion and Human–computer interaction. His studies deal with areas such as Machine learning, Polygon mesh and Action as well as Artificial intelligence. His Computer vision study combines topics in areas such as Representation and Benchmark.

His Object research incorporates themes from Feature extraction, Pattern recognition, Vertex, Algorithm and Reinforcement learning. In his study, Segmentation is strongly linked to Prior probability, which falls under the umbrella field of Feature extraction. Jitendra Malik is studying Training set, which is a component of Pattern recognition.

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

Normalized cuts and image segmentation

Jianbo Shi;J. Malik.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2000)

17616 Citations

Scale-space and edge detection using anisotropic diffusion

P. Perona;J. Malik.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1990)

15332 Citations

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Ross Girshick;Jeff Donahue;Trevor Darrell;Jitendra Malik.
computer vision and pattern recognition (2014)

14643 Citations

Shape matching and object recognition using shape contexts

S. Belongie;J. Malik;J. Puzicha.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)

7891 Citations

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

D. Martin;C. Fowlkes;D. Tal;J. Malik.
international conference on computer vision (2001)

5905 Citations

Contour Detection and Hierarchical Image Segmentation

P Arbeláez;M Maire;C Fowlkes;J Malik.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2011)

4080 Citations

Recovering high dynamic range radiance maps from photographs

Paul E. Debevec;Jitendra Malik.
international conference on computer graphics and interactive techniques (1997)

3261 Citations

Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach

Paul E. Debevec;Camillo J. Taylor;Jitendra Malik.
international conference on computer graphics and interactive techniques (1996)

2900 Citations

Learning to detect natural image boundaries using local brightness, color, and texture cues

D.R. Martin;C.C. Fowlkes;J. Malik.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

2595 Citations

Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons

Thomas Leung;Jitendra Malik.
International Journal of Computer Vision (2001)

1961 Citations

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