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D-Index & Metrics

Computer Science

D-Index
87
Citations
40868
World Ranking
706
National Ranking
371

Research.com Recognitions

  • 2013 - ACM Fellow For contributions to computer vision.

Overview

David Forsyth is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research focuses primarily on computer science and engineering, with a significant emphasis on computer vision and pattern recognition.

The main fields of study for Forsyth include:

  • Computer Science
  • Engineering

Within these fields, their work delves into several subfields such as:

  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence
  • Computational Mechanics
  • Ecology

Forsyth's research topics cover a wide range of areas, notably:

  • Generative Adversarial Networks and Image Synthesis
  • Advanced Vision and Imaging
  • Computer Graphics and Visualization Techniques
  • Advanced Image and Video Retrieval Techniques
  • 3D Shape Modeling and Analysis
  • Image Enhancement Techniques
  • Face recognition and analysis

They have published extensively, with a significant number of papers appearing in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • eLight
  • Australian field ornithology

Notable recent papers include:

  • "Polarization-based underwater geolocalization with deep learning," 2023, published in eLight
  • "Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval," 2021, presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal," 2024, available on arXiv (Cornell University)
  • "Cooperating RPN's Improve Few-Shot Object Detection," 2020, on arXiv (Cornell University)
  • "POVNet: Image-Based Virtual Try-On Through Accurate Warping and Residual," 2023, published in IEEE Transactions on Pattern Analysis and Machine Intelligence

Frequent collaborators in Forsyth's research include:

  • Min Jin Chong
  • Anand Bhattad
  • Kedan Li
  • Vaibhav Vavilala
  • Jeffrey Zhang

In recognition of their contributions to the field of computer vision, Forsyth was awarded the ACM Fellow distinction in 2013.

Best Publications

  • Computer Vision: A Modern Approach

    David A. Forsyth;Jean Ponce

  • Describing objects by their attributes

    Ali Farhadi;Ian Endres;Derek Hoiem;David Forsyth

  • Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary

    P. Duygulu;Kobus Barnard;J. F. G. de Freitas;David A. Forsyth

  • Matching words and pictures

    Kobus Barnard;Pinar Duygulu;David Forsyth;Nando de Freitas

  • Every picture tells a story: generating sentences from images

    Ali Farhadi;Mohsen Hejrati;Mohammad Amin Sadeghi;Peter Young

  • Generalizing motion edits with Gaussian processes

    Leslie Ikemoto;Okan Arikan;David Forsyth

  • A novel algorithm for color constancy

    D. A. Forsyth

  • Interactive motion generation from examples

    Okan Arikan;D. A. Forsyth

  • Utility data annotation with Amazon Mechanical Turk

    A. Sorokin;D. Forsyth

  • Learning the semantics of words and pictures

    K. Barnard;D. Forsyth

  • Finding Naked People

    Margaret M. Fleck;David A. Forsyth;Chris Bregler

  • Recovering the spatial layout of cluttered rooms

    Varsha Hedau;Derek Hoiem;David Forsyth

  • Invariant descriptors for 3D object recognition and pose

    D. Forsyth;J.L. Mundy;A. Zisserman;C. Coelho

  • Motion synthesis from annotations

    Okan Arikan;David A. Forsyth;James F. O'Brien

  • Names and faces in the news

    T.L. Berg;A.C. Berg;J. Edwards;M. Maire

  • Strike a pose: tracking people by finding stylized poses

    D. Ramanan;D.A. Forsyth;A. Zisserman

  • SafetyNet: Detecting and Rejecting Adversarial Examples Robustly

    Jiajun Lu;Theerasit Issaranon;David Forsyth

  • Finding and tracking people from the bottom up

    D. Ramanan;D.A. Forsyth

  • Thinking inside the box: using appearance models and context based on room geometry

    Varsha Hedau;Derek Hoiem;David Forsyth

  • Probabilistic Methods for Finding People

    S. Ioffe;D. A. Forsyth

  • Tracking People by Learning Their Appearance

    D. Ramanan;D.A. Forsyth;A. Zisserman

  • 计算机视觉 : Computer vision一种现代方法a modern approach英文版 / .

    David A. Forsyth;Jean Ponce

Frequent Co-Authors

Andrew Zisserman
Andrew Zisserman University of Oxford
Joseph L. Mundy
Joseph L. Mundy Brown University
Derek Hoiem
Derek Hoiem University of Illinois at Urbana-Champaign
Kobus Barnard
Kobus Barnard University of Arizona
Ali Farhadi
Ali Farhadi University of Washington
Jean Ponce
Jean Ponce École Normale Supérieure
Tamara L. Berg
Tamara L. Berg University of North Carolina at Chapel Hill
Jitendra Malik
Jitendra Malik University of California, Berkeley
Deva Ramanan
Deva Ramanan Carnegie Mellon University
Alexander G. Schwing
Alexander G. Schwing University of Illinois at Urbana-Champaign

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