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Pratul P. Srinivasan

Pratul P. Srinivasan

Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
38
Citations
18546
World Ranking
710
National Ranking
111

Computer Science

D-Index
38
Citations
24180
World Ranking
9928
National Ranking
4171

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Pratul P. Srinivasan is a researcher affiliated with Google in the United States. Their work is primarily situated in the fields of Computer Science and Engineering, with a notable focus on Computer Vision and Pattern Recognition, as well as Computer Graphics and Computer-Aided Design.

Their recent publications reflect contributions to various aspects of neural rendering and imaging techniques. Key papers include:

  • NeRF, 2021, Communications of the ACM
  • Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains, 2020, arXiv (Cornell University)
  • Block-NeRF: Scalable Large Scene Neural View Synthesis, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis, 2020, arXiv (Cornell University)

They have coauthored frequently with several researchers in their field, including:

  • Jonathan T. Barron
  • Ben Mildenhall
  • Dor Verbin
  • Peter Hedman
  • Matthew Tancik

Their publications have appeared in prominent venues, including:

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

Srinivasan's research spans several subfields of study, notably:

  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design
  • Computational Mechanics
  • Astronomy and Astrophysics
  • Environmental Engineering

The main topics of their work include:

  • Advanced Vision and Imaging
  • Computer Graphics and Visualization Techniques
  • 3D Shape Modeling and Analysis
  • Advanced Image Processing Techniques
  • Generative Adversarial Networks and Image Synthesis
  • Astrophysical Phenomena and Observations
  • Pulsars and Gravitational Waves Research

Best Publications

  • NeRF

    Unknown

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

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

  • Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields

    Jonathan T. Barron;Ben Mildenhall;Dor Verbin;Pratul P. Srinivasan

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

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

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

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

  • Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields

    Jonathan T. Barron;Ben Mildenhall;Matthew Tancik;Peter Hedman

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

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

  • Block-NeRF: Scalable Large Scene Neural View Synthesis

    Unknown

  • Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields

    Unknown

  • IBRNet: Learning Multi-View Image-Based Rendering

    Qianqian Wang;Zhicheng Wang;Kyle Genova;Pratul Srinivasan

  • HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Video

    Unknown

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

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

  • Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

    Pratul P. Srinivasan;Leo A. Kim;Priyatham S. Mettu;Scott W. Cousins

  • NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images

    Unknown

  • Dense Depth Priors for Neural Radiance Fields from Sparse Input Views

    Unknown

  • NeRFactor

    Unknown

  • NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis

    Pratul P. Srinivasan;Boyang Deng;Xiuming Zhang;Matthew Tancik

  • Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields

    Unknown

  • Pushing the Boundaries of View Extrapolation With Multiplane Images

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

  • Advances in Neural Rendering

    Ayush Tewari;Justus Thies;Ben Mildenhall;Pratul Srinivasan

  • Learning to Synthesize a 4D RGBD Light Field from a Single Image

    Pratul P. Srinivasan;Tongzhou Wang;Ashwin Sreelal;Ravi Ramamoorthi

  • Learned Initializations for Optimizing Coordinate-Based Neural Representations

    Matthew Tancik;Ben Mildenhall;Terrance Wang;Divi Schmidt

  • Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology

    Pratul P. Srinivasan;Stephanie J. Heflin;Joseph A. Izatt;Vadim Y. Arshavsky

  • Depth from shading, defocus, and correspondence using light-field angular coherence

    Michael W. Tao;Pratul P. Srinivasan;Jitendra Malik;Szymon Rusinkiewicz

  • Neural Reflectance Fields for Appearance Acquisition

    Sai Bi;Zexiang Xu;Pratul P. Srinivasan;Ben Mildenhall

  • Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination

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

  • Shape Estimation from Shading, Defocus, and Correspondence Using Light-Field Angular Coherence

    Michael W. Tao;Pratul P. Srinivasan;Sunil Hadap;Szymon Rusinkiewicz

  • Fully automatic software for retinal thickness in eyes with diabetic macular edema from images acquired by cirrus and spectralis systems.

    Joo Yong Lee;Stephanie J. Chiu;Pratul P. Srinivasan;Joseph A. Izatt

  • Advances in neural rendering

    A. Tewari;O. Fried;J. Thies;V. Sitzmann

  • Aperture Supervision for Monocular Depth Estimation

    Pratul P. Srinivasan;Rahul Garg;Neal Wadhwa;Ren Ng

Frequent Co-Authors

Jonathan T. Barron
Jonathan T. Barron Google (United States)
Ravi Ramamoorthi
Ravi Ramamoorthi University of California, San Diego
Sina Farsiu
Sina Farsiu Duke University
Noah Snavely
Noah Snavely Cornell University
Joseph A. Izatt
Joseph A. Izatt Duke University
Thomas Funkhouser
Thomas Funkhouser Google (United States)
Kalyan Sunkavalli
Kalyan Sunkavalli Adobe Systems (United States)
Paul Debevec
Paul Debevec Google (United States)
Justus Thies
Justus Thies Technical University of Munich

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