World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
40266
World Ranking
6273
National Ranking
250

Overview

Yuri Boykov is affiliated with the University of Waterloo in Canada and has a research focus primarily in the field of Computer Science.

Their work covers various subfields including:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Endocrinology, Diabetes and Metabolism
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics

Yuri Boykov's research topics involve:

  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • Medical Image Segmentation Techniques
  • Generative Adversarial Networks and Image Synthesis
  • Visual Attention and Saliency Detection
  • Human Pose and Action Recognition

Their recent papers include:

  • "Image Segmentation Using Deep Learning: A Survey," 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "RePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation," 2020, arXiv (Cornell University)
  • "Sparse Non-Local CRF With Applications," 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Sparse Non-local CRF," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Confluent Vessel Trees with Accurate Bifurcations," 2021, arXiv (Cornell University)

The venues where Yuri Boykov frequently publishes include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

The scientist collaborates regularly with several researchers, including:

  • Zhongwen Zhang
  • Dmitrii Marin
  • Shervin Minaee
  • Fatih Porikli
  • Antonio Plaza

Best Publications

  • Fast approximate energy minimization via graph cuts

    Y. Boykov;O. Veksler;R. Zabih

  • An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision

    Y. Boykov;V. Kolmogorov

  • Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images

    Y.Y. Boykov;M.-P. Jolly

  • Image Segmentation Using Deep Learning: A Survey.

    Shervin Minaee;Yuri Y. Boykov;Fatih Porikli;Antonio J Plaza

  • Graph Cuts and Efficient N-D Image Segmentation

    Yuri Boykov;Gareth Funka-Lea

  • Fast Approximate Energy Minimization with Label Costs

    Andrew Delong;Anton Osokin;Hossam N. Isack;Yuri Boykov

  • Markov random fields with efficient approximations

    Y. Boykov;O. Veksler;R. Zabih

  • Superpixels and supervoxels in an energy optimization framework

    Olga Veksler;Yuri Boykov;Paria Mehrani

  • Fast approximate energy minimization via graph cuts

    Y. Boykov;O. Veksler;R. Zabih

  • Energy-Based Geometric Multi-model Fitting

    Hossam Isack;Yuri Boykov

  • Interactive Organ Segmentation Using Graph Cuts

    Yuri Boykov;Marie-Pierre Jolly

  • Normalized Cut Loss for Weakly-Supervised CNN Segmentation

    Meng Tang;Abdelaziz Djelouah;Federico Perazzi;Yuri Boykov

  • Graph Cuts in Vision and Graphics: Theories and Applications

    Yuri Boykov;Olga Veksler

  • Constrained-CNN losses for weakly supervised segmentation.

    Hoel Kervadec;Jose Dolz;Meng Tang;Eric Granger

  • On Regularized Losses for Weakly-supervised CNN Segmentation

    Meng Tang;Federico Perazzi;Abdelaziz Djelouah;Ismail Ben Ayed

  • GrabCut in One Cut

    Meng Tang;Lena Gorelick;Olga Veksler;Yuri Boykov

  • What metrics can be approximated by geo-cuts, or global optimization of length/area and flux

    V. Kolmogorov;Y. Boykov

  • A variable window approach to early vision

    Yu. Boykov;O. Veksler;R. Zabih

  • A continuous max-flow approach to potts model

    Jing Yuan;Egil Bae;Xue-Cheng Tai;Yuri Boykov

  • Applications of parametric maxflow in computer vision

    V. Kolmogorov;Y. Boykov;C. Rother

  • for Optimal Boundary & Region Segmentation of Objects in N-D Images

    Yuri Y. Boykov;Marie-Pierre Jolly

Frequent Co-Authors

Olga Veksler
Olga Veksler University of Waterloo
Ismail Ben Ayed
Ismail Ben Ayed École de Technologie Supérieure
Victor Lempitsky
Victor Lempitsky Samsung (South Korea)
Vladimir Kolmogorov
Vladimir Kolmogorov Institute of Science and Technology Austria
Daniel Cremers
Daniel Cremers Technical University of Munich
Ramin Zabih
Ramin Zabih Cornell University
Fredrik Kahl
Fredrik Kahl Chalmers University of Technology
Xue-Cheng Tai
Xue-Cheng Tai NORCE Research
Milan Sonka
Milan Sonka University of Iowa

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