World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
72
Citations
27496
World Ranking
1645
National Ranking
847

Research.com Recognitions

  • 2018 - ACM Fellow For contributions to computer graphics, non-photorealistic rendering, computer animation, and machine learning
  • 2015 - ACM Distinguished Member
  • 2006 - Fellow of Alfred P. Sloan Foundation

Overview

Aaron Hertzmann is affiliated with Adobe Systems in the United States. Their research primarily focuses on computer science, with a strong emphasis on computer vision and pattern recognition, cognitive neuroscience, and computer graphics and computer-aided design. Additional fields of study include computational mechanics and human-computer interaction.

The scientist has contributed extensively to several research topics, including:

  • Aesthetic Perception and Analysis
  • Computer Graphics and Visualization Techniques
  • Advanced Vision and Imaging
  • Generative Adversarial Networks and Image Synthesis
  • 3D Shape Modeling and Analysis
  • Visual Attention and Saliency Detection
  • Human Pose and Action Recognition

Frequent publication venues for Aaron Hertzmann include:

  • arXiv (Cornell University)
  • Journal of Vision
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Computer Graphics and Applications
  • Perception

Recent papers published by Hertzmann cover a range of topics and years:

  • "Art and the science of generative AI", 2023, Science
  • "GANSpace: Discovering Interpretable GAN Controls", 2020, arXiv (Cornell University)
  • "LayoutGAN: Synthesizing Graphic Layouts With Vector-Wireframe Adversarial Networks", 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Why Do Line Drawings Work? A Realism Hypothesis", 2020, Perception
  • "Computers do not make art, people do", 2020, Communications of the ACM

Aaron Hertzmann has collaborated frequently with several co-authors, including:

  • Zoya Bylinskii
  • Shuicheng Yan
  • Laura Herman
  • Robert Pepperell
  • Olga Russakovsky

The scientist has received multiple awards, including the ACM Fellow recognition in 2018 for contributions to computer graphics, non-photorealistic rendering, computer animation, and machine learning. Additional honors include being named an ACM Distinguished Member in 2015 and a Fellow of the Alfred P. Sloan Foundation in 2006.

Best Publications

  • Removing camera shake from a single photograph

    Rob Fergus;Barun Singh;Aaron Hertzmann;Sam T. Roweis

  • Image analogies

    Aaron Hertzmann;Charles E. Jacobs;Nuria Oliver;Brian Curless

  • Gaussian Process Dynamical Models for Human Motion

    J.M. Wang;D.J. Fleet;A. Hertzmann

  • Recovering non-rigid 3D shape from image streams

    C. Bregler;A. Hertzmann;H. Biermann

  • Style-based inverse kinematics

    Keith Grochow;Steven L. Martin;Aaron Hertzmann;Zoran Popović

  • Painterly rendering with curved brush strokes of multiple sizes

    Aaron Hertzmann

  • Style machines

    Matthew Brand;Aaron Hertzmann

  • Illustrating smooth surfaces

    Aaron Hertzmann;Denis Zorin

  • Learning hatching for pen-and-ink illustration of surfaces

    Evangelos Kalogerakis;Derek Nowrouzezahrai;Simon Breslav;Aaron Hertzmann

  • Learning 3D mesh segmentation and labeling

    Evangelos Kalogerakis;Aaron Hertzmann;Karan Singh

  • Gaussian Process Dynamical Models

    Jack Wang;Aaron Hertzmann;David M. Blei

  • Recognizing Image Style.

    Sergey Karayev;Matthew Trentacoste;Helen Han;Aseem Agarwala

  • Nonrigid Structure-from-Motion: Estimating Shape and Motion with Hierarchical Priors

    L. Torresani;A. Hertzmann;C. Bregler

  • Shape and Spatially-Varying BRDFs from Photometric Stereo

    Dan B Goldman;Brian Curless;Aaron Hertzmann;Steven M Seitz

  • Controlling Perceptual Factors in Neural Style Transfer

    Leon A. Gatys;Alexander S. Ecker;Matthias Bethge;Aaron Hertzmann

  • GANSpace: Discovering Interpretable GAN Controls

    Erik Härkönen;Aaron Hertzmann;Jaakko Lehtinen;Jaakko Lehtinen;Sylvain Paris

  • Learning physics-based motion style with nonlinear inverse optimization

    C. Karen Liu;Aaron Hertzmann;Zoran Popović

  • Example-based photometric stereo: shape reconstruction with general, varying BRDFs

    A. Hertzmann;S.M. Seitz

  • Keyframe-based tracking for rotoscoping and animation

    Aseem Agarwala;Aaron Hertzmann;David H. Salesin;Steven M. Seitz

  • Priors for people tracking from small training sets

    R. Urtasun;D.J. Fleet;A. Hertzmann;P. Fua

Frequent Co-Authors

David J. Fleet
David J. Fleet University of Toronto
Steven M. Seitz
Steven M. Seitz University of Washington
Aseem Agarwala
Aseem Agarwala Adobe Systems (United States)
Hailin Jin
Hailin Jin Adobe Systems (United States)
Brian Curless
Brian Curless University of Washington
Evangelos Kalogerakis
Evangelos Kalogerakis Technical University of Crete
Ken Perlin
Ken Perlin New York University
Jimei Yang
Jimei Yang Adobe Systems (United States)
Eli Shechtman
Eli Shechtman Adobe Systems (United States)
Zoran Popović
Zoran Popović University of Washington

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