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D-Index & Metrics

Computer Science

D-Index
70
Citations
36163
World Ranking
1824
National Ranking
928

Research.com Recognitions

  • 2012 - Fellow of Alfred P. Sloan Foundation

Overview

Noah Snavely is a researcher affiliated with Cornell University in the United States. Their work primarily focuses on computer science, with a specialization in computer vision and pattern recognition. Their research spans multiple subfields including computer graphics and computer-aided design, computational mechanics, aerospace engineering, and plant science.

The scientist's main topics of work include advanced vision and imaging, computer graphics and visualization techniques, generative adversarial networks and image synthesis, advanced image and video retrieval techniques, 3D shape modeling and analysis, image enhancement techniques, and robotics and sensor-based localization.

Frequent coauthors of Noah Snavely include Zhengqi Li, Hadar Averbuch-Elor, Bharath Hariharan, Angjoo Kanazawa, and Ruojin Cai.

They have published extensively, with a concentrated presence in venues such as:

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

Some recent papers by Noah Snavely include:

  • NeRF++: Analyzing and Improving Neural Radiance Fields (2020), published in arXiv (Cornell University)
  • Unsupervised Semantic Segmentation by Distilling Feature Correspondences (2022), published in arXiv (Cornell University)
  • Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image (2021), presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • MetaSDF: Meta-learning Signed Distance Functions (2020), released via arXiv (Cornell University)
  • IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Noah Snavely was awarded a fellowship by the Alfred P. Sloan Foundation in 2012.

Best Publications

  • Photo tourism: exploring photo collections in 3D

    Noah Snavely;Steven M. Seitz;Richard Szeliski

  • Modeling the World from Internet Photo Collections

    Noah Snavely;Steven M. Seitz;Richard Szeliski

  • Unsupervised Learning of Depth and Ego-Motion from Video

    Tinghui Zhou;Matthew Brown;Noah Snavely;David G. Lowe

  • Building Rome in a day

    Sameer Agarwal;Yasutaka Furukawa;Noah Snavely;Ian Simon

  • Building Rome in a day

    Sameer Agarwal;Noah Snavely;Ian Simon;Steven M. Seitz

  • MegaDepth: Learning Single-View Depth Prediction from Internet Photos

    Zhengqi Li;Noah Snavely

  • Multi-View Stereo for Community Photo Collections

    M. Goesele;N. Snavely;B. Curless;H. Hoppe

  • Stereo magnification: learning view synthesis using multiplane images

    Tinghui Zhou;Richard Tucker;John Flynn;Graham Fyffe

  • Spacetime faces: high resolution capture for modeling and animation

    Li Zhang;Noah Snavely;Brian Curless;Steven M. Seitz

  • Deep Stereo: Learning to Predict New Views from the World's Imagery

    John Flynn;Ivan Neulander;James Philbin;Noah Snavely

  • IBRNet: Learning Multi-View Image-Based Rendering

    Qianqian Wang;Zhicheng Wang;Kyle Genova;Pratul Srinivasan

  • Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes

    Zhengqi Li;Simon Niklaus;Noah Snavely;Oliver Wang

  • Material recognition in the wild with the Materials in Context Database

    Sean Bell;Paul Upchurch;Noah Snavely;Kavita Bala

  • Bundle adjustment in the large

    Sameer Agarwal;Noah Snavely;Steven M. Seitz;Richard Szeliski

  • Location recognition using prioritized feature matching

    Yunpeng Li;Noah Snavely;Daniel P. Huttenlocher

  • NeRF++: Analyzing and Improving Neural Radiance Fields.

    Kai Zhang;Gernot Riegler;Noah Snavely;Vladlen Koltun

  • Worldwide pose estimation using 3d point clouds

    Yunpeng Li;Noah Snavely;Dan Huttenlocher;Pascal Fua

  • Scene Summarization for Online Image Collections

    I. Simon;N. Snavely;S.M. Seitz

  • DeepView: View Synthesis With Learned Gradient Descent

    John Flynn;Michael Broxton;Paul Debevec;Matthew DuVall

  • Intrinsic images in the wild

    Sean Bell;Kavita Bala;Noah Snavely

  • Discrete-continuous optimization for large-scale structure from motion

    David Crandall;Andrew Owens;Noah Snavely;Dan Huttenlocher

  • Robust Global Translations with 1DSfM

    Kyle Wilson;Noah Snavely

Frequent Co-Authors

Steven M. Seitz
Steven M. Seitz University of Washington
Kavita Bala
Kavita Bala Cornell University
Richard Szeliski
Richard Szeliski University of Washington
Sameer Agarwal
Sameer Agarwal Google (United States)
Brian Curless
Brian Curless University of Washington
Jonathan T. Barron
Jonathan T. Barron Google (United States)
David J. Crandall
David J. Crandall Indiana University
Serge Belongie
Serge Belongie University of Copenhagen

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