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Christoph Schnörr

Christoph Schnörr

D-Index & Metrics

Computer Science

D-Index
57
Citations
12661
World Ranking
3852
National Ranking
173

Overview

Christoph Schnörr is affiliated with Heidelberg University in Germany and has a substantial body of research work primarily in the fields of computer science and mathematics. Their work spans 75 publications in computer science and 25 in mathematics, reflecting a broad engagement across computational and theoretical domains.

Their research interests focus on several specialized areas, including:

  • Topological and Geometric Data Analysis
  • Markov Chains and Monte Carlo Methods
  • Medical Image Segmentation Techniques
  • Mathematical Biology Tumor Growth
  • Model Reduction and Neural Networks
  • Statistical Methods and Inference
  • Neural Networks and Applications

Christoph Schnörr's recent publications illustrate a strong involvement in image labeling, adaptive regularization, and segmentation techniques. Notable papers include:

  • Learning system parameters from Turing patterns (2023), published in Machine Learning
  • Learning Adaptive Regularization for Image Labeling Using Geometric Assignment (2020), published in Journal of Mathematical Imaging and Vision
  • Assignment flows for data labeling on graphs: convergence and stability (2021), published in Information Geometry
  • Assignment Flow for Order-Constrained OCT Segmentation (2021), published in International Journal of Computer Vision
  • Learning Linearized Assignment Flows for Image Labeling (2023), published in Journal of Mathematical Imaging and Vision

Their frequent coauthors highlight collaborative research across a network of scholars including Bastian Boll, Stefania Petra, Peter Albers, Jonathan Schwarz, and Daniel Gonzalez-Alvarado. These collaborations have contributed to a coherent research agenda centered on computational imaging and applied mathematics.

Publication venues where Christoph Schnörr regularly contributes feature reputed journals and repositories such as:

  • arXiv (Cornell University)
  • Journal of Mathematical Imaging and Vision
  • PAMM
  • Information Geometry
  • SIAM Journal on Imaging Sciences

Overall, Christoph Schnörr's work integrates advanced mathematical frameworks with practical applications in image analysis, pattern recognition, and computational theory. This profile reflects a comprehensive engagement with both foundational and applied scientific problems, contributing to knowledge in areas bridging artificial intelligence, computer vision, and statistical modeling.

Best Publications

  • Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods

    Andrés Bruhn;Joachim Weickert;Christoph Schnörr

  • Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional

    Daniel Cremers;Florian Tischhäuser;Joachim Weickert;Christoph Schnörr

  • A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion

    Joachim Weickert;Christoph Schnörr

  • Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint

    Joachim Weickert;Christoph Schnörr

  • Shape statistics in kernel space for variational image segmentation

    Daniel Cremers;Timo Kohlberger;Christoph Schnörr

  • Combined SVM-Based Feature Selection and Classification

    Julia Neumann;Christoph Schnörr;Gabriele Steidl

  • A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems

    Jorg H. Kappes;Bjoern Andres;Fred A. Hamprecht;Christoph Schnorr

  • Variational fluid flow measurements from image sequences: synopsis and perspectives

    Dominique Heitz;Etienne Mémin;Christoph Schnörr

  • Variational optical flow computation in real time

    A. Bruhn;J. Weickert;C. Feddern;T. Kohlberger

  • Nonlinear Shape Statistics in Mumford-Shah Based Segmentation

    Daniel Cremers;Timo Kohlberger;Christoph Schnörr

  • A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems

    Jörg H. Kappes;Bjoern Andres;Fred A. Hamprecht;Christoph Schnörr

  • Variational optical flow estimation for particle image velocimetry

    P. Ruhnau;T. Kohlberger;C. Schnörr;H. Nobach

  • A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods

    Andrés Bruhn;Joachim Weickert;Timo Kohlberger;Christoph Schnörr

  • Probabilistic subgraph matching based on convex relaxation

    Christian Schellewald;Christoph Schnörr

  • Towards recognition-based variational segmentation using shape priors and dynamic labeling

    Daniel Cremers;Nir Sochen;Christoph Schnörr

  • Convex Multi-class Image Labeling by Simplex-Constrained Total Variation

    Jan Lellmann;Jörg Kappes;Jing Yuan;Florian Becker

  • A Bayesian Framework for Multi-cue 3D Object Tracking

    Jan Giebel;Dariu Gavrila;Christoph Schnörr

  • Pedestrian Detection and Tracking Using a Mixture of View-Based Shape–Texture Models

    S. Munder;C. Schnorr;D.M. Gavrila

  • A Study of Parts-Based Object Class Detection Using Complete Graphs

    Martin Bergtholdt;Jörg Kappes;Stefan Schmidt;Christoph Schnörr

  • Spectral clustering of linear subspaces for motion segmentation

    Fabien Lauer;Christoph Schnorr

Frequent Co-Authors

Joachim Weickert
Joachim Weickert Saarland University
Daniel Cremers
Daniel Cremers Technical University of Munich
Andrés Bruhn
Andrés Bruhn University of Stuttgart
Karl Rohr
Karl Rohr Heidelberg University
Gerhard Reinelt
Gerhard Reinelt Heidelberg University
Fred A. Hamprecht
Fred A. Hamprecht Heidelberg University
Stefan Roth
Stefan Roth Technical University of Darmstadt
Anders Heyden
Anders Heyden Lund University
Joachim Hornegger
Joachim Hornegger University of Erlangen-Nuremberg
Etienne Mémin
Etienne Mémin French Institute for Research in Computer Science and Automation - INRIA

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