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D-Index & Metrics

Computer Science

D-Index
74
Citations
55170
World Ranking
1439
National Ranking
747

Research.com Recognitions

  • 2015 - IEEE Fellow For contributions to computer vision

Overview

David J. Kriegman is affiliated with the University of California, San Diego in the United States. Their research spans multiple main fields of study, including Medicine, Environmental Science, and Computer Science. Within these broader disciplines, their work encompasses several subfields such as Ecology, Ophthalmology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, and Global and Planetary Change.

The scientist has contributed to several key topics, notably Retinal Imaging and Analysis, Glaucoma and retinal disorders, Coral and Marine Ecosystems Studies, Marine and fisheries research, Computer Graphics and Visualization Techniques, Advanced Vision and Imaging, and Marine animal studies overview.

David J. Kriegman has published in a range of venues with multiple papers appearing in arXiv (Cornell University). Other publication venues include Ophthalmology Science, JAMA Ophthalmology, Limnology and Oceanography, and IEEE Transactions on Medical Imaging.

  • Neural Reflectance Fields for Appearance Acquisition, 2020, arXiv (Cornell University)
  • Detecting Glaucoma from Fundus Photographs Using Deep Learning without Convolutions, 2022, Ophthalmology Science
  • Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning, 2022, JAMA Ophthalmology
  • Rapid assessments of Pacific Ocean net coral reef carbonate budgets and net calcification following the 2014-2017 global coral bleaching event, 2022, Limnology and Oceanography
  • One-Vote Veto: Semi-Supervised Learning for Low-Shot Glaucoma Diagnosis, 2023, IEEE Transactions on Medical Imaging

Frequent collaborators include Rui Fan, Christopher Bowd, Mark Christopher, Nicole Brye, and Robert N. Weinreb. Each has coauthored multiple papers with Kriegman, indicating sustained research partnerships.

David J. Kriegman was named IEEE Fellow in 2015 for contributions related to computer vision. This recognition highlights part of their scientific focus within the fields of imaging and vision.

Best Publications

  • Eigenfaces vs. Fisherfaces: recognition using class specific linear projection

    P.N. Belhumeur;J.P. Hespanha;D.J. Kriegman

  • From few to many: illumination cone models for face recognition under variable lighting and pose

    A.S. Georghiades;P.N. Belhumeur;D.J. Kriegman

  • Detecting faces in images: a survey

    Ming-Hsuan Yang;D.J. Kriegman;N. Ahuja

  • Acquiring linear subspaces for face recognition under variable lighting

    Kuang-Chih Lee;J. Ho;D.J. Kriegman

  • Localizing Parts of Faces Using a Consensus of Exemplars

    Peter N. Belhumeur;David W. Jacobs;David J. Kriegman;Neeraj Kumar

  • The Bas-Relief Ambiguity

    Peter N. Belhumeur;David J. Kriegman;Alan L. Yuille

  • What Is the Set of Images of an Object Under All Possible Illumination Conditions

    Peter N. Belhumeur;David J. Kriegman

  • PSF estimation using sharp edge prediction

    N. Joshi;R. Szeliski;D.J. Kriegman

  • Clustering appearances of objects under varying illumination conditions

    J. Ho;Ming-Husang Yang;Jongwoo Lim;Kuang-Chih Lee

  • Video-based face recognition using probabilistic appearance manifolds

    Kuang-Chih Lee;J. Ho;Ming-Hsuan Yang;D. Kriegman

  • Image to Image Translation for Domain Adaptation

    Zak Murez;Soheil Kolouri;David Kriegman;Ravi Ramamoorthi

  • What is the set of images of an object under all possible lighting conditions

    P.N. Belhumeur;D.J. Kriegman

  • Structure and motion from line segments in multiple images

    C.J. Taylor;D.J. Kriegman

  • Stereo vision and navigation in buildings for mobile robots

    D.J. Kriegman;E. Triendl;T.O. Binford

  • From few to many: generative models for recognition under variable pose and illumination

    A.S. Georghiades;P.N. Belhumeur;D.J. Kriegman

  • Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation.

    Oscar Beijbom;Peter J. Edmunds;Chris Roelfsema;Jennifer Smith

  • Leginon: An Automated System for Acquisition of Images from Vitreous Ice Specimens

    Bridget Carragher;Nick Kisseberth;David Kriegman;Ronald A. Milligan

  • Face recognition using kernel eigenfaces

    M.-H. Yang;N. Ahuja;D. Kriegman

  • Appearance-based eye gaze estimation

    Kar-Han Tan;D.J. Kriegman;N. Ahuja

  • Automated annotation of coral reef survey images

    Oscar Beijbom;Peter J. Edmunds;David I. Kline;B. Greg Mitchell

  • Helmholtz Stereopsis: Exploiting Reciprocity for Surface Reconstruction

    Todd Zickler;Peter N. Belhumeur;David J. Kriegman

  • Illumination cones for recognition under variable lighting: faces

    A.S. Georghiades;D.J. Kriegman;P.N. Belhurneur

Frequent Co-Authors

Peter N. Belhumeur
Peter N. Belhumeur Columbia University
Jean Ponce
Jean Ponce École Normale Supérieure
Serge Belongie
Serge Belongie University of Copenhagen
Ming-Hsuan Yang
Ming-Hsuan Yang University of California, Merced
Todd Zickler
Todd Zickler Harvard University
Sameer Agarwal
Sameer Agarwal Google (United States)
Manmohan Chandraker
Manmohan Chandraker University of California, San Diego
Ravi Ramamoorthi
Ravi Ramamoorthi University of California, San Diego
Jongwoo Lim
Jongwoo Lim Seoul National University
B. Greg Mitchell
B. Greg Mitchell University of California, San Diego

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