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Computer Science

D-Index
77
Citations
29210
World Ranking
1248
National Ranking
664

Overview

Peyman Milanfar is affiliated with Google in the United States. Their academic contributions primarily focus on computer science, with a strong emphasis on computer vision and pattern recognition. Over the course of their career, they have published extensively in this domain.

The fields of study for their research include:

  • Computer Science

The subfields they work in are:

  • Computer Vision and Pattern Recognition
  • Media Technology
  • Artificial Intelligence
  • Computational Mechanics
  • Biomedical Engineering

The main topics covered in their work include:

  • Advanced Image Processing Techniques
  • Image and Signal Denoising Methods
  • Generative Adversarial Networks and Image Synthesis
  • Visual Attention and Saliency Detection
  • Image Enhancement Techniques
  • Image Processing Techniques and Applications
  • Advanced Image Fusion Techniques

Among their recent papers are:

  • MAXIM: Multi-Axis MLP for Image Processing (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Patch Craft: Video Denoising by Deep Modeling and Patch Matching (2021), presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • DVMark: A Deep Multiscale Framework for Video Watermarking (2023), published in IEEE Transactions on Image Processing
  • Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration (2023), published on arXiv (Cornell University)

Frequent co-authors who have collaborated with them include:

  • Mauricio Delbracio
  • Hossein Talebi
  • Zhengzhong Tu
  • Xiyang Luo
  • Yinxiao Li

The primary venues where their work appears most often are:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Image Processing
  • Frontiers in Signal Processing

Best Publications

  • Fast and robust multiframe super resolution

    S. Farsiu;M.D. Robinson;M. Elad;P. Milanfar

  • Kernel Regression for Image Processing and Reconstruction

    H. Takeda;S. Farsiu;P. Milanfar

  • NIMA: Neural Image Assessment

    Hossein Talebi;Peyman Milanfar

  • Advances and Challenges in Super-Resolution

    Sina Farsiu;M. Dirk Robinson;Michael Elad;Peyman Milanfar

  • Generalizing the Nonlocal-Means to Super-Resolution Reconstruction

    M. Protter;M. Elad;H. Takeda;P. Milanfar

  • Analysis versus synthesis in signal priors

    Michael Elad;Peyman Milanfar;Ron Rubinstein

  • The Little Engine That Could: Regularization by Denoising (RED)

    Yaniv Romano;Michael Elad;Peyman Milanfar

  • A Tour of Modern Image Filtering: New Insights and Methods, Both Practical and Theoretical

    P. Milanfar

  • Static and space-time visual saliency detection by self-resemblance.

    Hae Jong Seo;Peyman Milanfar

  • MAXIM: Multi-Axis MLP for Image Processing

    Unknown

  • A computationally efficient superresolution image reconstruction algorithm

    Nhat Nguyen;P. Milanfar;G. Golub

  • Is Denoising Dead

    P. Chatterjee;P. Milanfar

  • Automatic Parameter Selection for Denoising Algorithms Using a No-Reference Measure of Image Content

    Xiang Zhu;Peyman Milanfar

  • Multiframe demosaicing and super-resolution of color images

    S. Farsiu;M. Elad;P. Milanfar

  • Super-resolution imaging

    Peyman Milanfar

  • Super-Resolution Without Explicit Subpixel Motion Estimation

    H. Takeda;P. Milanfar;M. Protter;M. Elad

  • Clustering-Based Denoising With Locally Learned Dictionaries

    P. Chatterjee;P. Milanfar

  • Patch-Based Near-Optimal Image Denoising

    P. Chatterjee;P. Milanfar

  • Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement

    N. Nguyen;P. Milanfar;G. Golub

  • RAISR: Rapid and Accurate Image Super Resolution

    Yaniv Romano;John Isidoro;Peyman Milanfar

  • Fundamental performance limits in image registration

    D. Robinson;P. Milanfar

Frequent Co-Authors

Michael Elad
Michael Elad Technion – Israel Institute of Technology
Sina Farsiu
Sina Farsiu Duke University
Ali Shakouri
Ali Shakouri Purdue University West Lafayette
William Clement Karl
William Clement Karl Boston University
Joseph A. Izatt
Joseph A. Izatt Duke University
Michael P. Brenner
Michael P. Brenner University of Michigan–Ann Arbor
Michael K. Ng
Michael K. Ng Hong Kong Baptist University
Robert Nowak
Robert Nowak University of Wisconsin–Madison

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