World's Best Scientists 2026 revealed!
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Computer Science
Germany
2026

D-Index & Metrics

Computer Science

D-Index
116
Citations
66249
World Ranking
173
National Ranking
9

Research.com Recognitions

  • 2026 - Research.com Computer Science in Germany Leader Award
  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award

Overview

Daniel Cremers is affiliated with the Technical University of Munich in Germany. Their research primarily spans the fields of Computer Science and Engineering, with a particular focus on various subfields and topics within these areas.

Their main subfields of study include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Aerospace Engineering
  • Computational Mechanics
  • Geology

Main topics of their work cover:

  • Advanced Vision and Imaging
  • Robotics and Sensor-Based Localization
  • 3D Shape Modeling and Analysis
  • 3D Surveying and Cultural Heritage
  • Computer Graphics and Visualization Techniques
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques

Daniel Cremers has contributed to numerous publications, with recent papers highlighting advancements in multi-object tracking, visual-inertial odometry, semantic change segmentation, and neural radiance fields. Key recent papers include:

  • "MOT20: A benchmark for multi object tracking in crowded scenes" (2020), published in arXiv (Cornell University)
  • "DM-VIO: Delayed Marginalization Visual-Inertial Odometry" (2022), published in IEEE Robotics and Automation Letters
  • "DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation" (2022), published at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "E-NeRF: Neural Radiance Fields From a Moving Event Camera" (2023), published in IEEE Robotics and Automation Letters
  • "Trajectory prediction for intelligent vehicles using spatial-attention mechanism" (2020), published in IET Intelligent Transport Systems

The scientist has frequently published in venues such as:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • International Journal of Computer Vision
  • Lecture notes in computer science

Collaborations with other researchers are a notable part of their work. Frequent co-authors include:

  • Florian Bernard (20 publications)
  • Laura Leal-Taixé (17 publications)
  • Vladimir Golkov (16 publications)
  • Marvin Eisenberger (15 publications)
  • Lukas Koestler (15 publications)

Best Publications

  • LSD-SLAM: Large-Scale Direct Monocular SLAM

    Jakob Engel;Thomas Schöps;Daniel Cremers

  • FlowNet: Learning Optical Flow with Convolutional Networks

    Alexey Dosovitskiy;Philipp Fischery;Eddy Ilg;Philip Hausser

  • A benchmark for the evaluation of RGB-D SLAM systems

    Jrgen Sturm;Nikolas Engelhard;Felix Endres;Wolfram Burgard

  • Direct Sparse Odometry

    Jakob Engel;Vladlen Koltun;Daniel Cremers

  • A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

    Nikolaus Mayer;Eddy Ilg;Philip Hausser;Philipp Fischer

  • A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape

    Daniel Cremers;Mikael Rousson;Rachid Deriche

  • Dense visual SLAM for RGB-D cameras

    Christian Kerl;Jurgen Sturm;Daniel Cremers

  • FlowNet: Learning Optical Flow with Convolutional Networks

    Philipp Fischer;Alexey Dosovitskiy;Eddy Ilg;Philip Häusser

  • 3-D Mapping With an RGB-D Camera

    Felix Endres;Jurgen Hess;Jurgen Sturm;Daniel Cremers

  • An evaluation of the RGB-D SLAM system

    Felix Endres;Jurgen Hess;Nikolas Engelhard;Jurgen Sturm

  • One-Shot Video Object Segmentation

    S. Caelles;K. K. Maninis;J. Pont-Tuset;L. Leal-Taixe

  • The wave kernel signature: A quantum mechanical approach to shape analysis

    Mathieu Aubry;Ulrich Schlickewei;Daniel Cremers

  • FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture

    Caner Hazirbas;Lingni Ma;Csaba Domokos;Daniel Cremers

  • Robust odometry estimation for RGB-D cameras

    Christian Kerl;Jurgen Sturm;Daniel Cremers

  • Semi-dense Visual Odometry for a Monocular Camera

    Jakob Engel;Jürgen Sturm;Daniel Cremers

  • Large-scale direct SLAM with stereo cameras

    Jakob Engel;Jorg Stuckler;Daniel Cremers

  • An Improved Algorithm for TV-L1 Optical Flow

    Andreas Wedel;Thomas Pock;Christopher Zach;Horst Bischof

  • Image-Based Localization Using LSTMs for Structured Feature Correlation

    F. Walch;C. Hazirbas;L. Leal-Taixe;T. Sattler

  • An introduction to Total Variation for Image Analysis

    Antonin Chambolle;Vicent Caselles;Matteo Novaga;Daniel Cremers

  • MOT20: A benchmark for multi object tracking in crowded scenes.

    Patrick Dendorfer;Hamid Rezatofighi;Anton Milan;Javen Shi

  • Anisotropic Huber-L1 Optical Flow

    Manuel Werlberger;Werner Trobin;Thomas Pock;Andreas Wedel

Frequent Co-Authors

Thomas Brox
Thomas Brox University of Freiburg
Jürgen Sturm
Jürgen Sturm Google (United States)
Emanuele Rodolà
Emanuele Rodolà Sapienza University of Rome
Bodo Rosenhahn
Bodo Rosenhahn University of Hannover
Laura Leal-Taixé
Laura Leal-Taixé Technical University of Munich
Thomas Pock
Thomas Pock Graz University of Technology
Jörg Stückler
Jörg Stückler Max Planck Institute for Intelligent Systems
Christoph Schnörr
Christoph Schnörr Heidelberg University
Michael M. Bronstein
Michael M. Bronstein University of Oxford
Stefano Soatto
Stefano Soatto University of California, Los Angeles

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