World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
81
Citations
30748
World Ranking
1004
National Ranking
535

Research.com Recognitions

  • 2017 - ACM Fellow For contributions to computer graphics rendering and physics-based computer vision
  • 2017 - IEEE Fellow For contributions to foundations of computer graphics and computer vision
  • 2015 - ACM Distinguished Member
  • 2005 - Fellow of Alfred P. Sloan Foundation

Overview

Ravi Ramamoorthi is affiliated with the University of California, San Diego in the United States. Their research primarily spans computer science and engineering, with substantial contributions focused on computer vision and computer graphics.

Their main subfields of study include:

  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design
  • Computational Mechanics
  • Atomic and Molecular Physics, and Optics
  • Instrumentation

Ramamoorthi's research covers various topics, prominently featuring computer graphics and visualization techniques, advanced vision and imaging, and 3D shape modeling and analysis. Other significant topics in their work include image enhancement and advanced image processing techniques, generative adversarial networks and image synthesis, and face recognition and analysis.

The scientist has published extensively, with frequent contributions to leading venues such as:

  • arXiv (Cornell University)
  • ACM Transactions on Graphics
  • Computer Graphics Forum
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Some recent papers authored or coauthored by Ramamoorthi include:

  • NeRF, 2021, Communications of the ACM
  • Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains, 2020, arXiv (Cornell University)
  • NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis, 2020, arXiv (Cornell University)
  • Neural Reflectance Fields for Appearance Acquisition, 2020, arXiv (Cornell University)
  • Modulated Periodic Activations for Generalizable Local Functional Representations, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Frequent coauthors collaborating with Ramamoorthi include:

  • Zexiang Xu
  • Manmohan Chandraker
  • Sai Bi
  • Tiancheng Sun
  • Kai-En Lin

Recognized in their field, Ramamoorthi has received several awards including ACM Fellow and IEEE Fellow in 2017 for contributions to computer graphics and computer vision foundations. They were named an ACM Distinguished Member in 2015 and a Fellow of the Alfred P. Sloan Foundation in 2005.

Best Publications

  • NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

    Ben Mildenhall;Pratul P. Srinivasan;Matthew Tancik;Jonathan T. Barron

  • Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

    Matthew Tancik;Pratul P. Srinivasan;Ben Mildenhall;Sara Fridovich-Keil

  • Local light field fusion: practical view synthesis with prescriptive sampling guidelines

    Ben Mildenhall;Pratul P. Srinivasan;Rodrigo Ortiz-Cayon;Nima Khademi Kalantari

  • An efficient representation for irradiance environment maps

    Ravi Ramamoorthi;Pat Hanrahan

  • A signal-processing framework for inverse rendering

    Ravi Ramamoorthi;Pat Hanrahan

  • Learning-based view synthesis for light field cameras

    Nima Khademi Kalantari;Ting-Chun Wang;Ravi Ramamoorthi

  • Depth from Combining Defocus and Correspondence Using Light-Field Cameras

    Michael W. Tao;Sunil Hadap;Jitendra Malik;Ravi Ramamoorthi

  • Image to Image Translation for Domain Adaptation

    Zak Murez;Soheil Kolouri;David Kriegman;Ravi Ramamoorthi

  • Spacetime stereo: a unifying framework for depth from triangulation

    J. Davis;R. Ramamoorthi;S. Rusinkiewicz

  • Spacetime stereo: a unifying framework for depth from triangulation

    J. Davis;D. Nehab;R. Ramamoorthi;S. Rusinkiewicz

  • Efficiently combining positions and normals for precise 3D geometry

    Diego Nehab;Szymon Rusinkiewicz;James Davis;Ravi Ramamoorthi

  • Deep high dynamic range imaging of dynamic scenes

    Nima Khademi Kalantari;Ravi Ramamoorthi

  • On the relationship between radiance and irradiance: determining the illumination from images of a convex Lambertian object

    Ravi Ramamoorthi;Pat Hanrahan

  • All-frequency shadows using non-linear wavelet lighting approximation

    Ren Ng;Ravi Ramamoorthi;Pat Hanrahan

  • Occlusion-Aware Depth Estimation Using Light-Field Cameras

    Ting-Chun Wang;Alexei A. Efros;Ravi Ramamoorthi

  • Deep Stereo Using Adaptive Thin Volume Representation With Uncertainty Awareness

    Shuo Cheng;Zexiang Xu;Shilin Zhu;Zhuwen Li

  • Pushing the Boundaries of View Extrapolation With Multiplane Images

    Pratul P. Srinivasan;Richard Tucker;Jonathan T. Barron;Ravi Ramamoorthi

  • Analytic PCA construction for theoretical analysis of lighting variability in images of a Lambertian object

    R. Ramamoorthi

  • Triple product wavelet integrals for all-frequency relighting

    Ren Ng;Ravi Ramamoorthi;Pat Hanrahan

  • Learning to reconstruct shape and spatially-varying reflectance from a single image

    Zhengqin Li;Zexiang Xu;Ravi Ramamoorthi;Kalyan Sunkavalli

  • Frequency space environment map rendering

    Ravi Ramamoorthi;Pat Hanrahan

Frequent Co-Authors

Peter N. Belhumeur
Peter N. Belhumeur Columbia University
Shree K. Nayar
Shree K. Nayar Columbia University
Manmohan Chandraker
Manmohan Chandraker University of California, San Diego
Kalyan Sunkavalli
Kalyan Sunkavalli Adobe Systems (United States)
Henrik Wann Jensen
Henrik Wann Jensen University of California, San Diego
Maneesh Agrawala
Maneesh Agrawala Stanford University
Szymon Rusinkiewicz
Szymon Rusinkiewicz Princeton University
David J. Kriegman
David J. Kriegman University of California, San Diego

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