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Computer Science

D-Index
58
Citations
22337
World Ranking
3539
National Ranking
57

Overview

Shai Avidan is a researcher affiliated with Tel Aviv University in Israel, with a primary focus on computer science. The main fields of study in their work encompass Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Nature and Landscape Conservation, and Computational Mechanics.

The core topics addressed in their research include Adversarial Robustness in Machine Learning, Human Pose and Action Recognition, Advanced Image and Video Retrieval Techniques, Generative Adversarial Networks and Image Synthesis, Face Recognition and Analysis, Image and Signal Denoising Methods, and Video Surveillance and Tracking Methods.

Frequent coauthors working with Shai Avidan are Gabriel Brostow, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner, and Or Hirschorn.

Their publications have appeared regularly in several venues, notably arXiv (Cornell University), the 2021 International Conference on 3D Vision (3DV), the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Lecture Notes in Computer Science, and the Proceedings of the AAAI Conference on Artificial Intelligence.

Selected recent papers include:

  • Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Rethinking FUN: Frequency-Domain Utilization Networks, 2020, arXiv (Cornell University)
  • Aggregating Layers for Deepfake Detection, 2022, 2022 26th International Conference on Pattern Recognition (ICPR)
  • Geometric Adversarial Attacks and Defenses on 3D Point Clouds, 2021, 2021 International Conference on 3D Vision (3DV)
  • Optimize & Reduce: A Top-Down Approach for Image Vectorization, 2024, Proceedings of the AAAI Conference on Artificial Intelligence

Shai Avidan has also contributed extensively to book publications with Springer Science+Business Media, notably in volumes related to Computer Vision - ECCV 2022. Their contributions to this series consist of numerous chapters or sections published in 2022.

Best Publications

  • Fast Human Detection Using a Cascade of Histograms of Oriented Gradients

    Qiang Zhu;Mei-Chen Yeh;Kwang-Ting Cheng;S. Avidan

  • Seam carving for content-aware image resizing

    Shai Avidan;Ariel Shamir

  • Ensemble Tracking

    S. Avidan

  • Support vector tracking

    S. Avidan

  • Non-local Image Dehazing

    Dana Berman;Tali Treibitz;Shai Avidan

  • Improved seam carving for video retargeting

    Michael Rubinstein;Ariel Shamir;Shai Avidan

  • Locally Orderless Tracking

    Shaul Oron;Aharon Bar-Hillel;Dan Levi;Shai Avidan

  • Multi-operator media retargeting

    Michael Rubinstein;Ariel Shamir;Shai Avidan

  • Ensemble tracking

    S. Avidan

  • Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset

    Dana Berman;Deborah Levy;Shai Avidan;Tali Treibitz

  • Locally Orderless Tracking

    Shaul Oron;Aharon Bar-Hillel;Dan Levi;Shai Avidan

  • Layer extraction from multiple images containing reflections and transparency

    R. Szeliski;S. Avidan;P. Anandan

  • Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms

    Baback Moghaddam;Yair Weiss;Shai Avidan

  • Novel view synthesis in tensor space

    S. Avidan;A. Shashua

  • Trajectory triangulation: 3D reconstruction of moving points from a monocular image sequence

    S. Avidan;A. Shashua

  • FasT-Match: Fast Affine Template Matching

    Simon Korman;Daniel Reichman;Gilad Tsur;Shai Avidan

  • Single Image Dehazing Using Haze-Lines

    Dana Berman;Tali Treibitz;Shai Avidan

  • Object retrieval and localization with spatially-constrained similarity measure and k-NN re-ranking

    Xiaohui Shen;Zhe Lin;Jonathan Brandt;Shai Avidan

  • Coherency Sensitive Hashing

    Simon Korman;Shai Avidan

  • Novel view synthesis by cascading trilinear tensors

    S. Avidan;A. Shashua

  • The patch transform and its applications to image editing

    Taeg Sang Cho;M. Butman;S. Avidan;W.T. Freeman

  • Natural video matting using camera arrays

    Neel Joshi;Wojciech Matusik;Shai Avidan

Frequent Co-Authors

Amnon Shashua
Amnon Shashua Hebrew University of Jerusalem
Ariel Shamir
Ariel Shamir Reichman University
Hanspeter Pfister
Hanspeter Pfister Harvard University
Yair Weiss
Yair Weiss Hebrew University of Jerusalem
Josef Sivic
Josef Sivic Czech Technical University in Prague
Alexander M. Bronstein
Alexander M. Bronstein Technion – Israel Institute of Technology
Raja Giryes
Raja Giryes Tel Aviv University

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