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Computer Science

D-Index
43
Citations
10469
World Ranking
7842
National Ranking
3391

Overview

Christoph Rhemann is affiliated with Google in the United States and has a publication record reflecting contributions primarily in computer science, with a focus on computer vision and computer graphics.

Their research covers a range of topics, including:

  • Advanced Vision and Imaging
  • Computer Graphics and Visualization Techniques
  • Image Enhancement Techniques
  • Advanced Image Processing Techniques
  • Industrial Vision Systems and Defect Detection
  • Advanced Image and Video Retrieval Techniques

Their work has been published predominantly in the venue ACM Transactions on Graphics, with a total of four publications there, and arXiv (Cornell University), with two publications.

Some of their recent significant papers are:

  • Total relighting, 2021, ACM Transactions on Graphics
  • Light stage super-resolution, 2020, ACM Transactions on Graphics
  • Total relighting, 2021, ACM Transactions on Graphics
  • Light Stage Super-Resolution: Continuous High-Frequency Relighting, 2020, arXiv (Cornell University)
  • Deep relightable textures, 2020, ACM Transactions on Graphics

They frequently collaborate with a number of coauthors, including:

  • Sean Fanello
  • Paul Debevec
  • Sergio Orts Escolano
  • Chloe LeGendre
  • Christian Häne

Christoph Rhemann's contributions span subfields such as Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, and Industrial and Manufacturing Engineering.

Best Publications

  • Fast Cost-Volume Filtering for Visual Correspondence and Beyond

    A. Hosni;C. Rhemann;M. Bleyer;C. Rother

  • PatchMatch Stereo - Stereo Matching with Slanted Support Windows.

    Michael Bleyer;Christoph Rhemann;Carsten Rother

  • Fast cost-volume filtering for visual correspondence and beyond

    Christoph Rhemann;Asmaa Hosni;Michael Bleyer;Carsten Rother

  • Holoportation: Virtual 3D Teleportation in Real-time

    Sergio Orts-Escolano;Christoph Rhemann;Sean Fanello;Wayne Chang

  • Accurate, Robust, and Flexible Real-time Hand Tracking

    Toby Sharp;Cem Keskin;Duncan Robertson;Jonathan Taylor

  • Fusion4D: real-time performance capture of challenging scenes

    Mingsong Dou;Sameh Khamis;Yury Degtyarev;Philip Davidson

  • Real-time non-rigid reconstruction using an RGB-D camera

    Michael Zollhöfer;Matthias Nießner;Shahram Izadi;Christoph Rehmann

  • A perceptually motivated online benchmark for image matting

    Christoph Rhemann;Carsten Rother;Jue Wang;Margrit Gelautz

  • A global sampling method for alpha matting

    Kaiming He;Christoph Rhemann;Carsten Rother;Xiaoou Tang

  • StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction

    Sameh Khamis;Sean Ryan Fanello;Christoph Rhemann;Adarsh Kowdle

  • Local stereo matching using geodesic support weights

    Asmaa Hosni;Michael Bleyer;Margrit Gelautz;Christoph Rhemann

  • Single image portrait relighting

    Tiancheng Sun;Jonathan T. Barron;Yun-Ta Tsai;Zexiang Xu

  • The relightables: volumetric performance capture of humans with realistic relighting

    Kaiwen Guo;Peter Lincoln;Philip Davidson;Jay Busch

  • Motion2fusion: real-time volumetric performance capture

    Mingsong Dou;Philip Davidson;Sean Ryan Fanello;Sameh Khamis

  • Neural Light Transport for Relighting and View Synthesis

    Xiuming Zhang;Sean Fanello;Yun-Ta Tsai;Tiancheng Sun

  • MonoFusion: Real-time 3D reconstruction of small scenes with a single web camera

    Vivek Pradeep;Christoph Rhemann;Shahram Izadi;Christopher Zach

  • Improving Color Modeling for Alpha Matting

    Christoph Rhemann;Carsten Rother;Margrit Gelautz

  • HyperDepth: Learning Depth from Structured Light without Matching

    Sean Ryan Fanello;Christoph Rhemann;Vladimir Tankovich;Adarsh Kowdle

  • LookinGood: enhancing performance capture with real-time neural re-rendering

    Ricardo Martin-Brualla;Rohit Pandey;Shuoran Yang;Pavel Pidlypenskyi

  • Depth Super Resolution by Rigid Body Self-Similarity in 3D

    Michael Hornacek;Christoph Rhemann;Margrit Gelautz;Carsten Rother

  • ActiveStereoNet: Unsupervised End-to-End Learning for Active Stereo Systems

    Yinda Zhang;Sameh Khamis;Christoph Rhemann;Julien Valentin

Frequent Co-Authors

Shahram Izadi
Shahram Izadi Google (United States)
Sean Ryan Fanello
Sean Ryan Fanello Google (United States)
Carsten Rother
Carsten Rother Heidelberg University
Paul Debevec
Paul Debevec Google (United States)
David Kim
David Kim Microsoft (United States)
Pushmeet Kohli
Pushmeet Kohli DeepMind (United Kingdom)
Sing Bing Kang
Sing Bing Kang Zillow Group (United States)
Yinda Zhang
Yinda Zhang Google (United States)
Jonathan T. Barron
Jonathan T. Barron Google (United States)
Thomas Funkhouser
Thomas Funkhouser Google (United States)

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