World's Best Scientists 2026 revealed!
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Computer Science
USA
2026

D-Index & Metrics

Computer Science

D-Index
135
Citations
83590
World Ranking
87
National Ranking
54

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2012 - ACM Fellow For contributions to image processing and computer vision.
  • 2002 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to computer vision and image understanding.
  • 1998 - IEEE Fellow For contributions to computer vision, image processing and high performance computing.

Overview

Larry S. Davis is affiliated with the University of Maryland, College Park in the United States. Their research primarily falls within the domain of Computer Science, with a strong focus on Computer Vision and Pattern Recognition. Over their career, they have contributed to 146 publications in this field, including notable work in Artificial Intelligence and Computational Mechanics.

The primary subfields of study for Larry S. Davis include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computational Mechanics
  • Signal Processing
  • Aerospace Engineering

Their work spans several main topics, among which are:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Adversarial Robustness in Machine Learning

Larry S. Davis has frequently published in venues such as:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Lecture notes in computer science

Recent significant papers include:

  • "M3DETR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers," 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "Generate, Segment, and Refine: Towards Generic Manipulation Segmentation," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Rethinking Pseudo Labels for Semi-supervised Object Detection," 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • "A Dynamic Frame Selection Framework for Fast Video Recognition," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence

They have collaborated frequently with several co-authors, including:

  • Abhinav Shrivastava
  • Zuxuan Wu
  • Yu-Gang Jiang
  • Ser-Nam Lim
  • Shiyi Lan

Awards received by Larry S. Davis include recognition as an ACM Fellow in 2012 for contributions to image processing and computer vision, a Fellow of the International Association for Pattern Recognition (IAPR) in 2002 for contributions to computer vision and image understanding, and IEEE Fellow in 1998 for contributions to computer vision, image processing, and high performance computing.

Best Publications

  • W/sup 4/: real-time surveillance of people and their activities

    I. Haritaoglu;D. Harwood;L.S. Davis

  • Non-parametric Model for Background Subtraction

    Ahmed M. Elgammal;David Harwood;Larry S. Davis

  • An assessment of support vector machines for land cover classification

    C. Huang;L. S. Davis;J. R. G. Townshend

  • Background and foreground modeling using nonparametric kernel density estimation for visual surveillance

    A. Elgammal;R. Duraiswami;D. Harwood;L.S. Davis

  • Real-time foreground-background segmentation using codebook model

    Kyungnam Kim;Thanarat H. Chalidabhongse;David Harwood;Larry Davis

  • Soft-NMS — Improving Object Detection with One Line of Code

    Navaneeth Bodla;Bharat Singh;Rama Chellappa;Larry S. Davis

  • Model-based object pose in 25 lines of code

    Daniel F. Dementhon;Larry S. Davis

  • A survey of edge detection techniques

    Larry S. Davis

  • Label Consistent K-SVD: Learning a Discriminative Dictionary for Recognition

    Zhuolin Jiang;Zhe Lin;L. S. Davis

  • Learning Temporal Regularity in Video Sequences

    Mahmudul Hasan;Jonghyun Choi;Jan Neumann;Amit K. Roy-Chowdhury

  • 3-D model-based tracking of humans in action: a multi-view approach

    D.M. Gavrila;L.S. Davis

  • W/sup 4/: Who? When? Where? What? A real time system for detecting and tracking people

    I. Haritaoglu;D. Harwood;L.S. Davis

  • Robust real-time periodic motion detection, analysis, and applications

    R. Cutler;L.S. Davis

  • Learning a discriminative dictionary for sparse coding via label consistent K-SVD

    Zhuolin Jiang;Zhe Lin;Larry S. Davis

  • A large-scale benchmark dataset for event recognition in surveillance video

    Sangmin Oh;Anthony Hoogs;Amitha Perera;Naresh Cuntoor

  • W/sup 4/: A Real Time System for Detecting and Tracking People

    I. Haritaoglu;D. Harwood;L.S. Davis

  • NISP: Pruning Networks Using Neuron Importance Score Propagation

    Ruichi Yu;Ang Li;Chun-Fu Chen;Jui-Hsin Lai

  • An Analysis of Scale Invariance in Object Detection - SNIP

    Bharat Singh;Larry S. Davis

  • Learning Rich Features for Image Manipulation Detection

    Peng Zhou;Xintong Han;Vlad I. Morariu;Larry S. Davis

  • Human detection using partial least squares analysis

    William Robson Schwartz;Aniruddha Kembhavi;David Harwood;Larry S. Davis

  • Adversarial training for free

    Ali Shafahi;Mahyar Najibi;Mohammad Amin Ghiasi;Zheng Xu

Frequent Co-Authors

David Harwood
David Harwood University of Maryland, College Park
Ramani Duraiswami
Ramani Duraiswami University of Maryland, College Park
Daniel DeMenthon
Daniel DeMenthon Johns Hopkins University Applied Physics Laboratory
Zuxuan Wu
Zuxuan Wu Fudan University
Azriel Rosenfeld
Azriel Rosenfeld University of Maryland, College Park
Rama Chellappa
Rama Chellappa Johns Hopkins University
Zhe Lin
Zhe Lin Adobe Systems (United States)
Abhinav Gupta
Abhinav Gupta Carnegie Mellon University
Ross Cutler
Ross Cutler Microsoft (United States)
Bohyung Han
Bohyung Han Seoul National University

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