World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
44626
World Ranking
6628
National Ranking
2925

Research.com Recognitions

  • 2012 - ACM Fellow For contributions to discrete optimization in computer vision.

Overview

Ramin Zabih is affiliated with Cornell University in the United States and has a research focus primarily within the field of Computer Science. Their work spans subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Statistics and Probability, and Signal Processing.

The researcher has contributed to topics such as Domain Adaptation and Few-Shot Learning, Advanced Vision and Imaging, Topic Modeling, Adversarial Robustness in Machine Learning, Advanced Neural Network Applications, Machine Learning in Healthcare, and Advanced Image Processing Techniques.

Ramin Zabih's recent papers include:

  • "Pyramid Adversarial Training Improves ViT Performance", 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Deep survival analysis with longitudinal X-rays for COVID-19", 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selection", 2024, arXiv (Cornell University)
  • "AutoFlow: Learning a Better Training Set for Optical Flow", 2021, arXiv (Cornell University)
  • "Pyramid Adversarial Training Improves ViT Performance", 2021, arXiv (Cornell University)

Their work has been published frequently in venues such as arXiv (Cornell University), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV), and PubMed.

Frequent coauthors include:

  • Charles Herrmann
  • Richard Strong Bowen
  • Michele Santacatterina
  • Ce Liu
  • Michelle Shu

In recognition of their contributions to discrete optimization in computer vision, Ramin Zabih was awarded the ACM Fellow distinction in 2012.

Best Publications

  • Fast approximate energy minimization via graph cuts

    Y. Boykov;O. Veksler;R. Zabih

  • A taxonomy and evaluation of dense two-frame stereo correspondence algorithms

    D. Scharstein;R. Szeliski;R. Zabih

  • What energy functions can be minimized via graph cuts?

    Unknown

  • Image indexing using color correlograms

    Jing Huang;S.R. Kumar;M. Mitra;Wei-Jing Zhu

  • Non-parametric local transforms for computing visual correspondence

    Ramin Zabih;John Woodfill

  • Comparing images using joint histograms

    Greg Pass;Ramin Zabih

  • Computing visual correspondence with occlusions using graph cuts

    V. Kolmogorov;R. Zabih

  • A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors

    R. Szeliski;R. Zabih;D. Scharstein;O. Veksler

  • Comparing images using color coherence vectors

    Greg Pass;Ramin Zabih;Justin Miller

  • Multi-camera Scene Reconstruction via Graph Cuts

    Vladimir Kolmogorov;Ramin Zabih

  • A feature-based algorithm for detecting and classifying production effects

    Ramin Zabih;Justin Miller;Kevin Mai

  • Histogram refinement for content-based image retrieval

    G. Pass;R. Zabih

  • A feature-based algorithm for detecting and classifying scene breaks

    Ramin Zabih;Justin Miller;Kevin Mai

  • Markov random fields with efficient approximations

    Y. Boykov;O. Veksler;R. Zabih

  • Fast approximate energy minimization via graph cuts

    Y. Boykov;O. Veksler;R. Zabih

  • Spatial Color Indexing and Applications

    Jing Huang;S. Ravi Kumar;Mandar Mitra;Wei-Jing Zhu

  • A comparative study of energy minimization methods for markov random fields

    Richard Szeliski;Ramin Zabih;Daniel Scharstein;Olga Veksler

  • Bayesian multi-camera surveillance

    V. Kettnaker;R. Zabih

  • Efficient graph-based energy minimization methods in computer vision

    Ramin Zabih;Olga Veksler

  • Visual correspondence using energy minimization and mutual information

    Unknown

  • Exact voxel occupancy with graph cuts

    D. Snow;P. Viola;R. Zabih

  • A variable window approach to early vision

    Yu. Boykov;O. Veksler;R. Zabih

Frequent Co-Authors

Vladimir Kolmogorov
Vladimir Kolmogorov Institute of Science and Technology Austria
Olga Veksler
Olga Veksler University of Waterloo
Richard Szeliski
Richard Szeliski University of Washington
Yuri Boykov
Yuri Boykov University of Waterloo
Jiri Matas
Jiri Matas Czech Technical University in Prague
Nikos Paragios
Nikos Paragios CentraleSupélec
Endre Boros
Endre Boros Rutgers, The State University of New Jersey
David McAllester
David McAllester Toyota Technological Institute at Chicago
Ce Liu
Ce Liu Microsoft (United States)
Oussama Khatib
Oussama Khatib Stanford University

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