Publication

2025

  • Cassel, J. and Schlindwein, F. and Albers, P. and Schnörr, C., 10th Int. Conf. on Scale Space and Variational Methods in Computer Vision (SSVM); in press, Bundle Scale Spaces and Local Gauge Symmetries for Graph Networks, 2025
  • Gonzalez-Alvarado, D. and Schlindwein, F. and Cassel, J. and Steingruber, L. and Petra, S. and Schnörr, C., 10th Int. Conf. on Scale Space and Variational Methods in Computer Vision (SSVM); in press, Riemannian Patch Assignment Gradient Flows, 2025
  • Boll, B. and Gonzalez-Alvarado, D. and Petra, S. and Schnörr, C., J. Math. Imaging Vision; in press (preprint arXiv:2406.04527), Generative Assignment Flows for Representing and Learning Joint Distributions of Discrete Data, 2025,

2024

  • Cassel, J. and Boll, B. and Petra, S. and Albers, P. and Schnörr, C., preprint arXiv:2408.15946, pdf, Sigma Flows for Image and Data Labeling and Learning Structured Prediction, 2024,
  • Sorrenson, P. and Behrend-Uriarte, D. and Schnörr, C. and Köthe, U., preprint arXiv:2407.09297, pdf, Learning Distances from Data with Normalizing Flows and Score Matching, 2024,
  • Sanmart\'in, E. F. and Schnörr, C. and Hamprecht, F.A., preprint arXiv:2404.06447, pdf, The Central Spanning Tree Problem, 2024,
  • Savarino, F. and Albers, P. and Schnörr, C., Information Geometry, 1--31, pdf, On the Geometric Mechanics of Assignment Flows for Metric Data Labeling, 7, 2024,
  • Boll, B. and Gonzalez-Alvarado, D. and Petra, S. and Schnörr, C., preprint arXiv:2406.04527, pdf, Generative Assignment Flows for Representing and Learning Joint Distributions of Discrete Data, 2024,
  • Boll, B. and Gonzalez-Alvarado, D. and Schnörr, C., preprint arXiv:2402.07846, pdf, Generative Modeling of Discrete Joint Distributions by E-Geodesic Flow Matching on Assignent Manifolds, 2024,
  • Draxler, F. and Wahl, S. and Schnörr, C. and Köthe, U., ICML (preprint arXiv:2402.06578), pdf, On the Universality of Coupling-based Normalizing Flows, 2024,
  • Hans, M. and Kath, E. and Sparn, M. and Liebster, N. and Strobel, H. and Oberthaler, M. K. and Draxler, F. and Schnörr, C., Physical Review Research, pdf, Bose Einstein Condensate as Nonlinear Block of a Machine Learning Pipeline, 6, 2024
  • Boll, B. and Cassel, J. and Albers, P. and Petra, S. and Schnörr, C., preprint arXiv:2401.05918, pdf, A Geometric Embedding Approach to Multiple Games and Multiple Populations, 2024,

2023

  • Boll, B. and Schnörr, C., NeurIPS, pdf, On Certified Generalization in Structured Prediction, 2023,
  • Homeyer, C. and Schnörr, C., Proc. IEEE/CVF International Conference on Computer Vision, 880--891, pdf, On Moving Object Segmentation from Monocular Video with Transformers, 2023
  • Schwarz, J. and Cassel, J. and Boll, B. and Gärttner, M. and Albers, P. and Schnörr, C., Entropy, 1253, pdf, Quantum State Assignment Flows, 25, 2023,
  • Draxler, F. and Kühmichel, L. and Rousselot, A. and Müller, J. and Schnörr, C. and Köthe, U., ICML, pdf, On the Convergence Rate of Gaussianization with Random Rotations, 2023
  • Boll, B. and Zeilmann, A. and Petra, S. and Schnörr, C., PAMM: Proc. Appl. Math. Mech., e202200169, pdf, Self-Certifying Classification by Linearized Deep Assignment, 23, 2023,
  • Hans, M. and Kath, E. and Sparn, M. and Liebster, N. and Draxler, F. and Schnörr, C. and Strobel, H. and Oberthaler, M. K., Physical Review Letters, in press (preprint arXiv:2304.14905), pdf, Bose Einstein Condensate as Nonlinear Block of a Machine Learning Pipeline, 2023
  • Boll, B. and Schwarz, J. and Gonzalez-Alvarado, D. and Sitenko, D. and Petra, S. and Schn\"{o}rr, C., 9th Int. Conf. on Scale Space and Variational Methods in Computer Vision (SSVM), to appear, 730-742, pdf, LNCS, Modeling Large-scale Joint Distributions and Inference by Randomized Assignment, 14009, 2023
  • Schwarz, J. and Boll, B. and Sitenko, D. and Gonzalez-Alvarado, D. and Gärttner, M. and Albers, P. and Schn\"{o}rr, C., 9th Int. Conf. on Scale Space and Variational Methods in Computer Vision (SSVM), to appear, 743-756, pdf, LNCS, Quantum State Assignment Flows, 14009, 2023
  • Kahl, M. M. and Petra, S. and Schn\"{o}rr, C. and Steidl, G. and Zisler, M., 9th Int. Conf. on Scale Space and Variational Methods in Computer Vision (SSVM), to appear, 418-430, pdf, LNCS, On the Remarkable Efficiency of the SMART Iteration, 14009, 2023
  • Schnörr, D. and Schnörr, C., Machine Learning, 3151--3190, pdf, Learning System Parameters from Turing Patterns, 112, 2023,
  • Sitenko, D. and Boll, B. and Schnörr, C., SIAM J. Imaging Sciences, 501-567, pdf, A Nonlocal Graph-PDE and Higher-Order Geometric Integration for Image Labeling, 16, 2023,
  • Zeilmann, A. and Petra, S. and Schnörr, C., J. Math. Imag. Vision, 164--184, pdf, Learning Linearized Assignment Flows for Image Labeling, 65, 2023,

2022

  • Zern, A. and Zeilmann, A. and Schnörr, C., Information Geometry, 355--404, pdf, Assignment Flows for Data Labeling on Graphs: Convergence and Stability, 5, 2022,
  • Draxler, F. and Schnörr, C. and Köthe, U., NeuIPS, pdf, Whitening Convergence Rate of Coupling-based Normalizing Flows, 2022,
  • Sitenko, D. and Boll, B. and Schnörr, C., arXiv, SIAM J.~Imaging Sciences, pdf, A Nonlocal Graph-PDE and Higher-Order Geometric Integration for Image Labeling, in press, 2022,
  • Boll, B. and Zeilmann, A. and Petra, S. and Schnörr, C., preprint arXiv:2201.11162, pdf, Self-Certifying Classification by Linearized Deep Assignment, 2022,
  • Homeyer, C. and Lange, O. and Schnörr, C., ICPRAI, pdf, Multi-view Monocular Depth and Uncertainty Prediction with Deep SfM in Dynamic Environments, 2022,

2021

  • Savarino, F. and Albers, P. and Schnörr, C., preprint: arXiv, pdf, On the Geometric Mechanics of Assignment Flows for Metric Data Labeling, 2021,
  • Zern, A. and Zeilmann, A. and Schnörr, C., Information Geometry, pdf, Assignment Flows for Data Labeling on Graphs: Convergence and Stability, in press, 2021,
  • Sitenko, D. and Boll, B. and Schnörr, C., DAGM GCPR, pdf, Springer, LNCS, Assignment Flows and Nonlocal PDEs on Graphs, 2021
  • Gonzalez-Alvarado, D. and Zeilmann, A. and Schnörr, C., DAGM GCPR, pdf, Springer, LNCS, Quantifying Uncertainty of Image Labelings Using Assignment Flows, 2021
  • Sitenko, D. and Boll, B. and Schnörr, C., Int. J. Computer Vision, 3088--3118, pdf, Assignment Flow For Order-Constrained OCT Segmentation, 129, 2021,
  • Schnörr, D. and Schnörr, C., preprint: arXiv, pdf, Learning System Parameters from Turing Patterns, 2021,
  • Zeilmann, A. and Petra, S. and Schnörr, C., preprint: arXiv, pdf, Learning Linearized Assignment Flows for Image Labeling, 2021,
  • Savarino, F. and Schnörr, C., Europ. J. Appl. Math., 570--597, pdf, Continuous-Domain Assignment Flows (Special issue: Connections between Deep Learning and Partial Differential Equations), 32, 2021
  • Boll, B. and Schwarz, J. and Schnörr, C., SSVM 2021: Scale Space and Variational Methods in Computer Vision, 373-384, pdf, Springer, LNCS, On the Correspondence between Replicator Dynamics and Assignment Flows, 12679, 2021
  • Zeilmann, A. and Petra, S. and Schnörr, C., SSVM 2021: Scale Space and Variational Methods in Computer Vision, 385-397, pdf, Springer, LNCS, Learning Linear Assignment Flows for Image Labeling via Exponential Integration, 12679, 2021
  • Savarino, F. and Albers, P. and Schnörr, C., SSVM 2021: Scale Space and Variational Methods in Computer Vision, 398-410, pdf, Springer, LNCS, On the Geometric Mechanics of Assignment Flows for Metric Data Labeling, 12679, 2021
  • H\"{u}hnerbein, R. and Savarino, F. and Petra, S. and Schnörr, C., J. Math. Imaging Vision, 186--215, pdf, Learning Adaptive Regularization for Image Labeling Using Geometric Assignment, 63, 2021

2020

  • Sitenko, D. and Boll, B. and Schnörr, C., preprint: arXiv, pdf, Assignment Flow for Order-Constrained OCT Segmentation, 2020,
  • Draxler, F. and Schwarz, J. and Schnörr, C. and Köthe, U., GCPR, pdf, Characterizing The Role of A Single Coupling Layer in Affine Normalizing Flows, 2020
  • Schwarz, J. and Draxler, F. and Köhte, U. and Schnörr, C., GCPR, pdf, Riemannian SOS-Polynomial Normalizing Flows, 2020
  • Sitenko, D. and Boll, B. and Schnörr, C., GCPR, pdf, Assignment Flow for Order-Constrained OCT Segmentation, 2020
  • Savarino, F. and Schnörr, C., Europ. J. Appl. Math., Continuous-Domain Assignment Flows, 2020,
  • H\"{u}hnerbein, R. and Savarino, F. and Petra, S. and Schnörr, C., J. Math. Imaging Vision, pdf, Learning Adaptive Regularization for Image Labeling Using Geometric Assignment, 2020,
  • Zisler, M. and Zern, A. and Petra, S. and Schnörr, C., SIAM Journal on Imaging Sciences, 1113--1156, pdf, Self-Assignment Flows for Unsupervised Data Labeling on Graphs, 13, 2020,
  • Schnörr, C., Handbook of Variational Methods for Nonlinear Geometric Data, Grohs, P. and Holler, M. and Weinmann, A., 235---260, pdf, Springer, Assignment Flows, 2020,
  • Censor, Y. and Petra, S. and Schnörr, C., J. Appl. Numer. Optimization (in press; arXiv:1911.05498), 15-62, pdf, Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case, 2, 2020,
  • Zern, A. and Zisler, M. and Petra, S. and Schnörr, C., Journal of Mathematical Imaging and Vision, 982-1006, pdf, Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment, 62, 2020,
  • Zeilmann, A. and Savarino, F. and Petra, S. and Schn\"{o}rr, C., Inverse Problems, 034004 (33pp), pdf, Geometric Numerical Integration of the Assignment Flow, 36, 2020
  • Desana, M. and Schnörr, C., Machine Learning, 135--173, pdf, Sum-Product Graphical Models, 109, 2020

2019

  • Censor, Y. and Petra, S. and Schnörr, C., preprint: arXiv, pdf, Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case, 2019,
  • Zisler, M. and Zern, A. and Petra, S. and Schnörr, C., preprint: arXiv, pdf, Self-Assignment Flows for Unsupervised Data Labeling on Graphs, 2019,
  • H\"{u}hnerbein, R. and Savarino, F. and Petra, S. and Schnörr, C., preprint: arXiv, pdf, Learning Adaptive Regularization for Image Labeling Using Geometric Assignment, 2019,
  • Kostrykin, L. and Schnörr, C. and Rohr, K., Medical Image Analysis, Globally Optimal Segmentation of Cell Nuclei in Fluoroscence Microscopy Images using Shape and Intensity Information, 2019,
  • Desana, M. and Schnörr, C., Machine Learning, Sum-Product Graphical Models, 2019,
  • Zeilmann, A. and Savarino, F. and Petra, S. and Schn\"{o}rr, C., Inverse Problems, Geometric Numerical Integration of the Assignment Flow, 2019,
  • Rathke, F. and Schnörr, C., Comp. Statistics \& Data Analysis, 41--58, Fast Multivariate Log-Concave Density Estimation, 140, 2019
  • Zern, A. and Zisler, M. and Petra, S. and Schnörr, C., preprint: arXiv, pdf, Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment, 2019,
  • Savarino, F. and Schnörr, C., Proc. SSVM, pdf, Springer, A Variational Perspective on the Assignment Flow, 2019
  • Zisler, M. and Zern, A. and Petra, S. and Schnörr, C., Proc. SSVM, pdf, Springer, Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment, 2019
  • H\"{u}hnerbein, R. and Savarino, F. and Petra, S. and Schnörr, C., Proc. SSVM, pdf, Springer, Learning Adaptive Regularization for Image Labeling Using Geometric Assignment, 2019

2018

  • Zeilmann, A. and Savarino, F. and Petra, S. and Schn\"{o}rr, C., preprint: arXiv, pdf, Geometric Numerical Integration of the Assignment Flow, 2018,
  • Zern, A. and Zisler, M. and Astr\"{o}m, F. and Petra, S. and Schn\"{o}rr, C., GCPR, pdf, Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment, 2018
  • H\"{u}hnerbein, R. and Savarino, F. and Astr\"{o}m, F. and Schn\"{o}rr, C., SIAM J.~Imaging Science, 1317--1362, pdf, Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment, 11, 2018,
  • Rathke, F. and Schnörr, C., preprint: arXiv, Fast Multivariate Log-Concave Density Estimation, 2018,
  • Zern, A. and Rohr, K. and Schn\"{o}rr, C., EMMCVPR, 533--547, pdf, LNCS, Geometric Image Labeling with Global Convex Labeling Constraints, 10746, 2018
  • Kostrykin, L. and Schnörr, C. and Rohr, K., Proc.~ISBI, pdf, Segmentation of Cell Nuclei Using Intensity-Based Model Fitting and Sequential Convex Programming, 2018

2017

  • Aström, F. and Schnörr, C., Comp.~Vision Image Understanding, 43--59, pdf, A Geometric Approach for Color Image Regularization, 165, 2017,
  • Hühnerbein, R. and Savarino, F. and Aström, F. and Schnörr, C., pdf, Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment, 2017,
  • Zern, A. and Rohr, K. and Schnörr, C., Proc.~EMMCVPR, Geometric Image Labeling with Global Convex Labeling Constraints, 2017
  • Zisler, M. and Savarino, F. and Petra, S. and Schnörr, C., Proc.~GCPR, pdf, Gradient Flows on a Riemannian Submanifold for Discrete Tomography, 2017
  • Bodnariuc, E. and Petra, S. and Schnörr, C. and Voorneveld, J., Proc.~GCPR, pdf, A Local Spatio-Temporal Approach to Plane Wave Ultrasound Particle Image Velocimetry, 2017
  • Rathke, F. and Desana, M. and Schnörr, C., Proc.~MICCAI, pdf, Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans, 2017
  • Dalitz, R. and Petra, S. and Schnörr, C., Proc.~SSVM, pdf, Springer, LNCS, Compressed Motion Sensing, 10302, 2017
  • Savarino, F. and Hühnerbein, R. and Aström, F. and Recknagel, J. and Schnörr, C., Proc.~SSVM, pdf, Springer, LNCS, Numerical Integration of Riemannian Gradient Flows for Image Labeling, 10302, 2017
  • Aström, F. and Hühnerbein, R. and Savarino, F. and Recknagel, J. and Schnörr, C., Proc.~SSVM, pdf, Springer, LCNS, MAP Image Labeling Using Wasserstein Messages and Geometric Assignment, 10302, 2017
  • Zisler, M. and Aström, F. and Petra, S. and Schnörr, C., Proc.~SSVM, pdf, Springer, LNCS, Image Reconstruction by Multilabel Propagation, 10302, 2017
  • Markowsky, P. and Reith, S. and Zuber, T.E. and König, R. and Rohr, K. and Schnörr, C., Proc.~ISBI, pdf, Segmentation of cell structure using model-based set covering with iterative reweighting, 2017
  • Aström, F. and Petra, S. and Schmitzer, B. and Schnörr, C., J.~Math.~Imag.~Vision, 211--238, Image Labeling by Assignment, 58, 2017,
  • Berger, J. and Lenzen, F. and Becker, F. and Neufeld, A. and Schnörr, C., J.~Math.~Imag.~Vision, 102--129, pdf, {Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations}, 58, 2017

2016

  • Silvestri, F. and Reinelt, G. and Schnörr, C., Symmetry-free SDP Relaxations for Affine Subspace Clustering, 2016,
  • Aström, F. and Petra, S. and Schmitzer, B. and Schnörr, C., Proc.~ECCV, pdf, A Geometric Approach to Image Labeling, 2016
  • Aström, F. and Schnörr, C., Proc.~ECCV, pdf, Double-Opponent Vectorial Total Variation, 2016
  • Bodnariuc, E. and Petra, S. and Poelma, C. and Schnörr, C., Proc.~CGPR, pdf, Parametric Dictionary-Based Velocimetry for Echo PIV, 2016
  • Zisler, M. and Petra, S. and Schnörr, Cl. and Schnörr, Ch., Proc.~GCPR, pdf, Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints, 2016
  • Berger, Johannes and Schnörr, Christoph, 38th German Conference on Pattern Recognition, pdf, Joint Recursive Monocular Filtering of Camera Motion and Disparity Map, 2016
  • Censor, Y. and Gibali, A. and Lenzen, F. and Schnörr, C., J.~Comp.~Math., 608-623, pdf, The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising, 34, 2016
  • Aström, F. and Schnörr, C., A Geometric Approach to Color Image Regularization, 2016,
  • Aström, F. and Petra, S. and Schmitzer, B. and Schnörr, C., Proc.~2nd Int.~Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award), The Assignment Manifold: A Smooth Model for Image Labeling, 2016
  • Desana, M. and Schnörr, C., pdf, Expectation Maximization for Sum-Product Networks as Exponential Family Mixture Models, 2016,
  • Kappes, J.H. and Swoboda, P. and Savchynskyy, B. and Hazan, T. and Schnörr, C., J.~Math.~Imag.~Vision, 221--237, pdf, Multicuts and Perturb \& MAP for Probabilistic Graph Clustering, 56, 2016
  • Zisler, M. and Kappes, J.H. and Schnörr, Cl. and Petra, S. and Schnörr, Ch., IEEE Comp.~Imaging, 335-347, Non-Binary Discrete Tomography by Continuous Non-Convex Optimization, 2, 2016
  • Aström, F. and Petra, S. and Schmitzer, B. and Schnörr, C., pdf, Image Labeling by Assignment, 2016,
  • Kappes, J. and Speth, M. and Reinelt, G. and Schnörr, C., Comp.~Vision Image Understanding, 104--119, pdf, Higher-order Segmentation via Multicuts, 143, 2016
  • Swoboda, P. and Shekhovtsov, A. and Kappes, J.H. and Schnörr, C. and Savchynskyy, B., IEEE Trans.~Patt.~Anal.~Mach.~Intell., 1370--1382, pdf, Partial Optimality by Pruning for MAP-Inference with General Graphical Models, 38, 2016

2015

  • Kappes, J.H. and Petra, S. and Schnörr, C. and Zisler, M., Proc.~GCPR, pdf, TomoGC: Binary Tomography by Constrained Graph Cuts, 2015
  • Silvestri, F. and Reinelt, G. and Schnörr, C., Proc.~GCPR, pdf, A Convex Relaxation Approach to the Affine Subspace Clustering Problem, 2015
  • Didden, E.-M. and Thorarinsdottir, T.L. and Lenkoski, A. and Schnörr, C., Image Anal.~Stereol., 161-170, pdf, Shape from Texture using Locally Scaled Point Processes, 34, 2015
  • Gianniotis, N. and Schnörr, C. and Molkenthin, C. and Bora, S.S., Patt.~Anal.~Appl., pdf, Approximate variational inference based on a finite sample of Gaussian latent variables, 2015,
  • Berger, Johannes and Neufeld, Andreas and Becker, Florian and Lenzen, Frank and Schnörr, Christoph, Scale Space and Variational Methods in Computer Vision (SSVM 2015), pdf, Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations, 2015
  • Berger, Johannes and Lenzen, Frank and Becker, Florian and Neufeld, Andreas and Schnörr, Christoph, pdf, Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations, 2015,
  • Biesdorf, A. and Wörz, S. and von Tengg-Kobligk, H. and Rohr, K. and Schnörr, C., Proc.~ISBI, pdf, 3D Segmentation of Vessels by Incremental Implicit Polynomial Fitting and Convex Optimization, 2015
  • Bodnariuc, E. and Gurung, A. and Petra, S. and Schnörr, C., Proc.~EMMCVPR, 378--391, pdf, Springer, LNCS, Adaptive Dictionary-Based Spatio-temporal Flow Estimation for Echo PIV, 8932, 2015
  • Kappes, J.H. and Andres, B. and Hamprecht, F.A. and Schnörr, C. and Nowozin, S. and Batra, D. and Kim, S. and Kausler, B.X. and Kröger, T. and Lellmann, J. and Komodakis, N. and Savchynskyy, B. and Rother, C., Int.~J.~Comp.~Vision, 155-184, pdf, A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, 115, 2015
  • Kappes, J. and Swoboda, P. and Savchynskyy, B. and Hazan , T. and Schnörr, C., Proc.~SSVM, pdf, Springer, LNCS, Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts, 2015
  • Lenzen, Frank and Berger, Johannes, pdf, LNCS, Solution-Driven Adaptive Total Variation Regularization, 2015
  • Neufeld, Andreas and Berger, Johannes and Becker, Florian and Lenzen, Frank and Schnörr, Christoph, 37th German Conference on Pattern Recognition, pdf, Estimating Vehicle Ego-Motion and Piecewise Planar Scene Structure from Optical Flow in a Continuous Framework, 2015
  • Rathke, F. and Schnörr, C., An. St. Univ. Ovidius Constanta, 151-166, pdf, A Computational Approach to Log-Concave Density Estimation, 23, 2015
  • Schmitzer, B. and Schnörr, C., J.~Math.~Imag.~Vision, 436--458, pdf, Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes, 52, 2015,

2014

  • Becker, Florian and Petra, Stefania and Schnörr, Christoph, Handbook of Mathematical Methods in Imaging, Scherzer, O., Springer, Optical Flow, 2014
  • Denitiu, A. and Petra, S. and Schnörr, Cl. and Schnörr, Ch., Fundamenta Informaticae, 73--102, pdf, Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections, 135, 2014
  • Denitiu, Andreea and Petra, Stefania and Schnörr, Claudius and Schnörr, Christoph, Discrete Geometry for Computer Imagery (DGCI) 2014, Barcucci,Elena and Frosini,Andrea and Eds Rinaldi,Simone, 262--274, pdf, Springer, LNCS, An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography, 2014
  • Kappes, Jörg Hendrik and Beier, Thorsten and Schnörr, Christoph, International Workshop on Graphical Models in Computer Vision, pdf, MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves, 2014
  • Jörg H. Kappes and Bjoern Andres and Fred A. Hamprecht and Christoph Schnörr and Sebastian Nowozin and Dhruv Batra and Sungwoong Kim and Bernhard X. Kausler and Thorben Kröger and Jan Lellmann and Nikos Komodakis and Bogdan Savchynskyy and Carsten Rother, CoRR, pdf, A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, abs/1404.0533, 2014,
  • Kröger, Thorben and Kappes, Jörg H. and Beier, Thorsten and Köthe, Ullrich and Hamprecht, Fred A., 36th German Conference on Pattern Recognition, Asymmetric Cuts: Joint Image Labeling and Partitioning, 2014
  • Lenzen, F. and Lellmann, J. and Becker, F. and Schnörr, C., SIAM J.~Imag.~Sci., 2139--2174, pdf, Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets, 7, 2014
  • Petra, S. and Schnörr, C., Linear Algebra and its Applications, 168-198, pdf, Average Case Recovery Analysis of Tomographic Compressive Sensing, 441, 2014
  • Rathke, F. and Schmidt, S. and Schnörr, C., Medical Image Analysis, 781-794, pdf, Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization, 18, 2014
  • Schäfer, Henrik and Lenzen, Frank and Garbe, Christoph S., Optics Express, 29835-29846, Model based scattering correction in time-of-flight cameras, 22, 2014
  • Bernhard Schmitzer and Christoph Schnörr, pdf, Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes, 2014
  • Swoboda, Paul and Savchynskyy, Bogdan and Kappes, Jörg H. and Schnörr, Christoph, IEEE Conference on Computer Vision and Pattern Recognition 2014, pdf, Partial Optimality by Pruning for MAP-inference with General Graphical Models, 2014

2013

  • Becker, Florian and Lenzen, Frank and Kappes, Jörg H. and Schnörr, Christoph, International Journal of Computer Vision, 269--297, pdf, Springer US, Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences, 105, 2013,
  • Breitenreicher, Dirk and Lellmann, Jan and Schnörr, Christoph, Optimization Methods and Software, 1081-1094, pdf, COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis, 28, 2013, ,
  • Kappes, Jörg H. and Andres, Bjoern and Hamprecht, Fred~A. and Schnörr, Christoph and Nowozin, Sebastian and Batra, Dhruv and Kim, Sungwoong and Kausler, Bernhard X. and Lellmann, Jan and Komodakis, Nikos and Rother, Carsten, CVPR, pdf, A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem, 2013
  • Jörg H. Kappes and Markus Speth and Gerhard Reinelt and Christoph Schnörr, CVPR, pdf, Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization, 2013
  • Kappes, Jörg Hendrik and Speth, Markus and Reinelt, Gerhard and Schnörr, Christoph, ArXiv e-prints, pdf, Higher-order Segmentation via Multicuts, 2013
  • Damien Lefloch and Rahul Nair and Frank Lenzen and Henrik Schäfer and Lee Streeter and Michael J. Cree and Reinhard Koch and Andreas Kolb, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, Grzegorzek, Marcin and Theobalt, Christian and Koch, Reinhard and Kolb, Andreas, 3-24, Springer, Lecture Notes in Computer Science, Technical Foundation and Calibration Methods for Time-of-Flight Cameras, 8200, 2013
  • Lellmann, J. and Lellmann, B. and Widmann, F. and Schnörr, C., Int.~J.~Comp.~Visionz, 241-269, pdf, Discrete and Continuous Models for Partitioning Problems, 104, 2013
  • Lenzen, Frank and Becker, Florian and Lellmann, Jan, Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013, 371--398, pdf, Springer, LNCS, Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities, 54, 2013
  • Lenzen, Frank and Becker, Florian and Lellmann, Jan and Petra, Stefania and Schnörr, Christoph, Computational Optimization and Applications, 371-398, pdf, Springer Netherlands, A class of quasi-variational inequalities for adaptive image denoising and decomposition, 54, 2013,
  • Lenzen, Frank and Kim, Kwang In and Schäfer, Henrik and Nair, Rahul and Meister, Stephan and Becker, Florian and Garbe, Christoph~S. and Theobalt, Christian, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, Grzegorzek, Marcin and Theobalt, Christian and Koch, Reinhard and Kolb, Andreas, 25-45, pdf, Springer, Lecture Notes in Computer Science, Denoising Strategies for Time-of-Flight Data, 8200, 2013
  • Nair, Rahul and Ruhl, Kai and Lenzen, Frank and Meister, Stephan and Schäfer, Henrik and Garbe, Christoph~S. and Eisemann, Martin and Magnor, Marcus and Kondermann, Daniel, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, Grzegorzek, Marcin and Theobalt, Christian and Koch, Reinhard and Kolb, Andreas, 105-127, pdf, Springer, Lecture Notes in Computer Science, A Survey on Time-of-Flight Stereo Fusion, 8200, 2013
  • Petra, Stefania and Schnörr, Christoph and Becker, Florian and Lenzen, Frank, Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013, 110-124, pdf, Springer, LNCS, B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems, 7893, 2013
  • Petra, S. and Schnörr, C. and Schröder, A., Fundamenta Informaticae, 285--312, pdf, Critical Parameter Values and Reconstruction Propertiesof Discrete Tomography: Application to Experimental FluidDynamics, 125, 2013
  • Savchynskyy, Bogdan and Kappes, Jörg Hendrik and Swoboda, Paul and Schnörr, Christoph, NIPS, pdf, Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation, 2013
  • Schäfer, Henrik and Lenzen, Frank and Garbe, Christoph.~S., 3DV-Conference, 2013 International Conference on, 111-118, pdf, Depth and Intensity Based Edge Detection in Time-of-Flight Images, 2013,
  • Bernhard Schmitzer and Christoph Schnörr, Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2013), 123-136, pdf, Object Segmentation by Shape Matching with Wasserstein Modes, 2013
  • Bernhard Schmitzer and Christoph Schnörr, Journal of Mathematical Imaging and Vision, 143-159, pdf, Modelling convex shape priors and matching based on the Gromov-Wasserstein distance, 46, 2013
  • Bernhard Schmitzer and Christoph Schnörr, pdf, Contour Manifolds and Optimal Transport, 2013
  • Bernhard Schmitzer and Christoph Schnörr, Scale Space and Variational Methods (SSVM 2013), 452-464, pdf, A Hierarchical Approach to Optimal Transport, 2013
  • Paul Swoboda and Bogdan Savchynskyy and Jörg H. Kappes and Christoph Schnörr, Scale Space and Variational Methods (SSVM 2013), pdf, Partial Optimality via Iterative Pruning for the Potts Model, 2013
  • Paul Swoboda and Christoph Schnörr, Energy Minimization Methods in Computer Vision and Pattern Recognition, Anders Heyden and Fredrik Kahl and Carl Olsson and Magnus Oskarsson and Xue-Cheng Tai, 321--334, pdf, Springer, Lecture Notes in Computer Science, Variational Image Segmentation and Cosegmentation with the Wasserstein Distance, 8081, 2013
  • Swoboda, P. and Schnörr, C., SIAM J.~Imag.~Sci., 1719-1735, pdf, Convex Variational Image Restoration with Histogram Priors, 6, 2013

2012

  • Andres, Björn and Beier, Thorsten and Kappes, Jörg H., ArXiv e-prints, pdf, OpenGM: A C++ Library for Discrete Graphical Models, 2012
  • Björn Andres and Jörg Hendrik Kappes and Thorsten Beier and Ullrich Köthe and Fred~A. Hamprecht, ECCV 2012, pdf, The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models, 2012
  • Becker, Florian and Wieneke, Bernhard and Petra, Stefania and Schröder, Andreas and Schnörr, Christoph, IEEE Transactions on Image Processing, 3053 -- 3065, pdf, Variational Adaptive Correlation Method for Flow Estimation, 21, 2012,
  • Jörg Hendrik Kappes and Bogdan Savchynskyy and Christoph Schnörr, CVPR, pdf, A Bundle Approach To Efficient MAP-Inference by Lagrangian Relaxation, 2012
  • Lellmann, Jan and Lenzen, Frank and Schnörr, Christoph, Journal of Mathematical Imaging and Vision, 239-257, pdf, Springer, Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem, 47, 2012,
  • Lenzen, Frank and Becker, Florian and Lellmann, Jan and Petra, Stefania and Schnörr, Christoph, Proceedings of the 3rd International Conference on Scale Space and Variational Methods in Computer Vision 2011, LNCS, 206-217, pdf, Springer, Variational Image Denoising with Adaptive Constraint Sets, 2012
  • Nair, Rahul and Lenzen, Frank and Meister, Stephan and Schäfer, Henrik and Garbe, Christoph~S. and Kondermann, Daniel, Computer Vision--ECCV 2012. Workshops and Demonstrations, 1--11, pdf, Springer Berlin Heidelberg, High accuracy TOF and stereo sensor fusion at interactive rates, 2012
  • Petra, S. and Schnörr, C. and Schröder, A., Critical Parameter Values and Reconstruction Properties of Discrete Tomography: Application to Experimental Fluid Dynamics, 2012,
  • Bogdan Savchynskyy and Stefan Schmidt and Jörg Hendrik Kappes and Christoph Schnörr, UAI 2012, pdf, Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing, 2012
  • Bernhard Schmitzer and Christoph Schnörr, Scale Space and Variational Methods (SSVM 2011), 423-434, pdf, Weakly Convex Coupling Continuous Cuts and Shape Priors, 2012

2011

  • Björn Andres and Jörg H. Kappes and Thorsten Beier and Ullrich Köthe and Fred~A. Hamprecht, Proceedings of ICCV, pdf, Probabilistic Image Segmentation with Closedness Constraints, 2011
  • Becker, Florian and Lenzen, Frank and Kappes, Jörg H. and Schnörr, Christoph, 2011 IEEE International Conference on Computer Vision (ICCV), 1692 -- 1699, pdf, Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences, 2011,
  • Breitenreicher, Dirk and Lellmann, Jan and Schnörr, Christoph, Advances in Adaptive Data Analysis, 149-166, pdf, Sparse Template-Based Variational Image Segmentation, 3, 2011
  • Breitenreicher, Dirk and Schnörr, Christoph, Int.~J.~Comp.~Vision, 32--52, pdf, Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data, 92, 2011, ,
  • Jörg Hendrik Kappes and Markus Speth and Björn Andres and Gerhard Reinelt and Christoph Schnörr, EMMCVPR, pdf, Springer, Globally Optimal Image Partitioning by Multicuts, 2011
  • Heidelberg, Germany, Jörg Hendrik Kappes, Inference on Highly-Connected Discrete Graphical Models with Applications to Visual Object Recognition, 2011,
  • Lellmann, Jan and Lenzen, Frank and Schnörr, Christoph, Energy Min. Meth. Comp. Vis. Patt. Recogn., Boykov, Y. and Kahl, F. and Lempitsky, V. F. and Schmidt, F. R., 132--146, pdf, Springer, LNCS, Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem, 6819, 2011
  • Lellmann, Jan and Lenzen, Frank and Schnörr, Christoph, Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem, 2011,
  • Lellmann, J. and Schnörr, C., CoRR, Continuous Multiclass Labeling Approaches and Algorithms, abs/1102.5448, 2011,
  • Lellmann, J. and Schnörr, C., Control Systems and Computers, 43--54, Regularizers for Vector-Valued Data and Labeling Problems in Image Processing, 2, 2011
  • Lellmann, J. and Schnörr, C., SIAM J.~Imag.~Sci., 1049-1096, pdf, Continuous Multiclass Labeling Approaches and Algorithms, 4, 2011
  • Nicola, A. and Petra, S. and Popa, C. and Schnörr, C., Int.~J.~Comp.~Math., pdf, A general extending and constraining procedure for linear iterative methods, 2011,
  • Fabian Rathke and Stefan Schmidt and Christoph Schnörr, MICCAI, Fichtinger, Gabor and Martel, Anne L. and Peters, Terry M., 370--377, pdf, Springer, Lecture Notes in Computer Science, Order Preserving and Shape Prior Constrained Intra-Retinal Layer Segmentation in Optical Coherence Tomography, 6893, 2011
  • Savchynskyy, B. and Kappes, J. H. and Schmidt, S. and Schnörr, C., IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pdf, A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling, 2011
  • Stefan Schmidt and Bogdan Savchynskyy and Jörg Hendrik Kappes and Christoph Schnörr, EMMCVPR, 89-103, pdf, Springer, LNCS, Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization, 6819, 2011

2010

  • Andres, Björn and Kappes, Jörg H. and Köthe, Ullrich and Schnörr, Christoph and Hamprecht, Fred~A., Pattern Recognition, Proc.~32th DAGM Symposium, pdf, An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM, 2010
  • Bergtholdt, Martin and Kappes, Jörg H. and Schmidt, Stefan and Schnörr, Christoph, Int.~J.~Comp.~Vision, 93-117, pdf, A Study of Parts-Based Object Class Detection Using Complete Graphs, 87, 2010, ,
  • Breitenreicher, Dirk and Schnörr, Christoph, Machine Vision and Applications, 601-611, pdf, Robust 3D object registration without explicit correspondence using geometric integration, 21, 2010, ,
  • Heitz, D. and Mémin, E. and Schnörr, C., Exp.~Fluids, 369-393, pdf, Variational fluid flow measurements from image sequences: synopsis and perspectives, 48, 2010
  • Kappes, J. H. and Schmidt, S. and Schnörr, C., European Conference on Computer Vision (ECCV), Daniilidis, K. and Maragos, P. and Paragios, N., 735--747, pdf, Springer Berlin / Heidelberg, MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation, 6313, 2010
  • Lellmann, J. and Breitenreicher, D. and Schnörr, C., European Conference on Computer Vision (ECCV), Daniilidis, K. and Maragos, P. and Paragios, N., 494--505, pdf, Springer Berlin / Heidelberg, LNCS, Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision, 6312, 2010
  • Lellmann, J. and Schnörr, C., Continuous Multiclass Labeling Approaches and Algorithms, 2010,
  • Vlasenko, A. and Schnörr, C., IEEE Trans.~Image Proc., 586-595, pdf, Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates, 19, 2010

2009

  • Heidelberg, Germany, Becker, Florian, Variational Correlation and Decomposition Methods for Particle Image Velocimetry, 2009,
  • Breitenreicher, Dirk and Schnörr, Christoph, Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009), Cremers, D. and Boykov, Y. and Blake, A. and Schmidt, F. R., 274-287, pdf, Springer, LNCS, Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence, 5681, 2009,
  • Christian Gosch, Contour Methods for View Point Tracking, 2009,
  • Kyoto, Japan, Lauer, F. and Schnörr, C., Proc.~IEEE Int.~Conf.~Computer Vision (ICCV'09), pdf, Spectral Clustering of Linear Subspaces for Motion Segmentation, 2009
  • Lellmann, J. and Becker, F. and Schnörr, C., IEEE International Conference on Computer Vision (ICCV), 646 -- 653, pdf, Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers, 2009
  • Lellmann, J. and Kappes, J. H. and Yuan, J. and Becker, F. and Schnörr, C., Scale Space and Variational Methods in Computer Vision (SSVM 2009), Tai, X.-C. and Mórken, K. and Lysaker, M. and Lie, K.-A., 150-162, pdf, Springer, LNCS, Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation, 5567, 2009
  • Nicola, A. and Petra, S. and Popa, C. and Schnörr, C., pdf, On a general extending and constraining procedure for linear iterative methods, 2009,
  • Petra, S. and Popa, C. and Schnörr, C., pdf, Accelerating Constrained SIRT with Applications in Tomographic Particle Image Reconstruction, 2009,
  • Petra, S. and Schnörr, C., pdf, TomoPIV meets Compressed Sensing, 2009,
  • Petra, S. and Schnörr, C., Pure Math.~Appl., 49 -- 76, pdf, TomoPIV meets Compressed Sensing, 20, 2009,
  • Petra, S. and Schröder, A. and Schnörr, C., Imaging Measurement Methods for Flow Analysis, Nitsche, W. and Dobriloff, C., 63-72, pdf, Springer, Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 3D Tomography from Few Projections in Experimental Fluid Mechanics, 106, 2009
  • Vlasenko, A. and Schnörr, C., Imaging Measurement Methods for Flow Analysis, Nitsche, W. and Dobriloff, C., 247-256, pdf, Springer, Notes on Numerical Fluid Mechanics and Multidisciplinary Design, Variational Approaches for Model-Based PIV and Visual Fluid Analysis, 106, 2009
  • Yuan, Jing and Schnörr, Christoph and Steidl, Gabriele, J.~Math.~Imag.~Vision, 169-177, pdf, Convex Hodge Decomposition and Regularization of Image Flows, 33, 2009
  • Yuan, Jing. and Schnörr, Christoph and Steidl, Gabriele, Scale Space and Variational Methods in Computer Vision (SSVM 2009), Tai, X.-C. and Mórken, K. and Lysaker, M. and Lie, K.-A., 552-564, pdf, Springer, LNCS, Total-Variation Based Piecewise Affine Regularization, 5567, 2009

2008

  • Becker, Florian and Schnörr, Christoph, Pattern Recognition -- 30th DAGM Symposium, 325--334, pdf, Springer Verlag, LNCS, Decomposition of Quadratric Variational Problems, 5096, 2008
  • Becker, Florian and Wieneke, Bernhard and Yuan, Jing and Schnörr, Christoph, Pattern Recognition -- 30th DAGM Symposium, 335--344, pdf, Springer Verlag, LNCS, A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry, 5096, 2008
  • Becker, Florian and Wieneke, Bernhard and Yuan, Jing and Schnörr, Christoph, 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 1.1.3, pdf, Variational Correlation Approach to Flow Measurement with Window Adaption, 2008
  • Markus Enzweiler and Dariu M. Gavrila, IEEE~Transactions~on~Pattern~Analysis~and~Machine~Intelligence, available online: IEEE Computer Society Digital Library, http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.260, Monocular Pedestrian Detection: Survey and Experiments, 2008
  • Markus Enzweiler and Dariu M. Gavrila, Proc.~Int.~Conf.~Comp.~Vision and Patt.~Recog.~(CVPR), A Mixed Generative-Discriminative Framework for Pedestrian Classification, 2008
  • Markus Enzweiler and Pascal Kanter and Dariu M. Gavrila, Proc.~IEEE~Symposium~on~Intelligent~Vehicles, 792-797, Monocular Pedestrian Recognition Using Motion Parallax, 2008
  • Ketut Fundana and Anders Heyden and Christian Gosch and Christoph Schnörr, 19th Int.~Conf.~Patt.~Recog.~(ICPR), 1--4, pdf, Continuous Graph Cuts for Prior-Based Object Segmentation, 2008
  • Gosch, Christian and Fundana, Ketut and Heyden, Anders and Schnörr, Christoph, Computer Vision -- ECCV 2008, 251--263, pdf, Springer, LNCS, View Point Tracking of Rigid Object Based on Shape Sub-Manifolds, 5302, 2008
  • Kappes, J. H. and Schnörr, C., Pattern Recognition -- 30th DAGM Symposium, 1--10, pdf, Springer Verlag, LNCS, MAP-Inference for Highly-Connected Graphs with DC-Programming, 5096, 2008
  • Lellmann, J. and Kappes, J.~H. and Yuan, J. and Becker, F. and Schnörr, C., pdf, Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation, 2008,
  • Munder, S. and Schnörr, C. and Gavrila, D. M., IEEE Trans.~Intell.~Transp.~Systems, 333-343, Pedestrian Detection and Tracking Using a Mixture of View-Based Shape-Texture Models, 9, 2008
  • Stefania Petra and Constantin Popa and Christoph Schnörr, pdf, Extended and Constrained Cimmino-type Algorithms with Applications in Tomographic Image Reconstruction, 2008,
  • Constanta, Romania, Petra, S. and Popa, C. and Schnörr, C., Proc.~7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM~08), pdf, Ed Acad Romane, Bucuresti, Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods, 2008
  • Bucharest, Romania, Petra, S. and Popa, C. and Schnörr, C., Proc. 7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 08), Ed Acad Romane, Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods, 2008
  • Petra, S. and Schröder, A. and Wieneke, B. and Schnörr, C., Pattern Recognition -- 30th DAGM Symposium, 294--303, pdf, Springer Verlag, LNCS, On Sparsity Maximization in Tomographic Particle Image Reconstruction, 5096, 2008
  • Vlasenko, A. and Schnörr, C., Pattern Recognition -- 30th DAGM Symposium, 406--415, pdf, Springer Verlag, LNCS, Physically Consistent Variational Denoising of Image Fluid Flow Estimates, 5096, 2008
  • Yuan, Jing and Steidl, Gabriele and Schnörr, Christoph, Pattern Recognition -- 30th DAGM Symposium, 416--425, pdf, Springer Verlag, LNCS, Convex Hodge Decomposition of Image Flows, 5096, 2008

2007

  • Gall, Jürgen and Potthoff, Jürgen and Schnörr, Christoph and Rosenhahn, Bodo and Seidel, Hans-Peter, J.~Math.~Imag.~Vision, 1--18, pdf, Interacting and Annealing Particle Filters: Mathematics and a Recipe for Applications, 28, 2007
  • Karim, R. and Bergtholdt, M. and Kappes, J. H. and Schnörr, C., Pattern Recognition -- 29th DAGM Symposium, 395-404, pdf, Springer, LCNS, Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification, 4713, 2007
  • Constanta, Romania, Petra, S. and Schnörr, C. and A. Schröder and B.~Wieneke, Proc.~6th Workshop on Modelling of Environmental and Life Sciences Problems (WMM~07), pdf, Ed Acad Romane, Bucuresti, Tomographic Image Reconstruction in Experimental Fluid Dynamics: Synopsis and Problems, 2007
  • Ruhnau, P. and Schnörr, C., Exp.~in Fluids, 61--78, pdf, Optical Stokes Flow Estimation: An Imaging-Based Control Approach, 42, 2007
  • Ruhnau, P. and Stahl, A. and Schnörr, C., Measurement Science and Technology, 755-763, pdf, Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization, 18, 2007
  • Schellewald, C. and Roth, S. and Schnörr, C., Image Vision Comp., 1301--1314, pdf, Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views, 25, 2007
  • Schmidt, S. and Kappes, J. H. and Bergtholdt, M. and Pekar, V. and Dries, S. and Bystrov, D. and Schnörr, C., Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007), 122-133, pdf, Springer, LCNS, Spine Detection and Labeling Using a Parts-Based Graphical Model, 4584, 2007
  • Schnörr, C., Computing, 137-160, pdf, Signal and Image Approximation with Level-Set Constraints, 81, 2007
  • Boston, Schnörr, C. and Schüle, T. and Weber, S., Advances in Discrete Tomography and Its Applications, Herman, G. and Kuba, A., Birkhäuser, Variational Reconstruction with DC-Programming, 2007
  • Welk, M. and Weickert, J. and Becker, F. and Schnörr, C. and Feddern, C. and Burgeth, B., Signal Processing, 291-308, pdf, Median and related local filters for tensor-valued images, 87, 2007
  • Yuan, J. and Schnörr, C. and Mémin, E., J.~Math.~Imag.~Vision, 67-80, pdf, Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation, 28, 2007
  • Yuan, J. and Schnörr, C. and Steidl, G., SIAM J.~Scientific Computing, 2283-2304, pdf, Simultaneous Optical Flow Estimation and Decomposition, 29, 2007
  • Hamprecht, Fred~A. and Schnörr, Christoph and Jähne, Bernd, Springer, LCNS, Pattern Recognition -- 29th DAGM Symposium, 4713, 2007

2006

  • Bergtholdt, Martin and Kappes, Jörg H. and Schnörr, Christoph, Proc.~DAGM 2006, 375-388, pdf, Springer, LCNS, Learning of Graphical Models and Efficient Inference for Object Class Recognition, 375-388, 2006
  • Bruhn, Andrés and Weickert, Joachim and Kohlberger, Timo and Schnörr, Christoph, Int.~J.~Computer Vision, 257-277, pdf, A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods, 70, 2006
  • Cremers, Daniel and Sochen, Nir and Schnörr, Christoph, IJCV, 67-81, Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation, 66, 2006
  • Heiler, M. and Schnörr, C., Computer Vision -- ECCV 2006, 56-67, pdf, Springer, LNCS, Controlling Sparseness in Non-negative Tensor Factorization, 3951, 2006
  • Heiler, M. and Schnörr, C., J.~Mach.~Learning Res., 1385--1407, Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming, 7, 2006,
  • Ruhnau, P. and Stahl, A. and Schnörr, C., Proc.~DAGM 2006, 375-388, pdf, Springer, LNCS, On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization, 375-388, 2006
  • A. Stahl and P. Ruhnau and C. Schnörr, ECCV 2006, International Workshop on The Representation and Use of Prior Knowledge in Vision, pdf, LNCS, Springer, A Distributed Parameter Approach to Dynamic Image Motion, 2006
  • Weber, S. and Nagy, A. and Schüle, T. and Schnörr, C. and Kuba, A., Discrete Geometry for Computer Imagery (DGCI 2006), 146-156, pdf, Springer, LNCS, A Benchmark Evaluation of Large-Scale Optimization Approaches to Binary Tomography, 4245, 2006
  • Weber, S. and Schüle, T. and Schnörr, C. and Kuba, A., Combinatorial Image Analysis, 375-388, pdf, Springer, Lect.~Not.~Comp.~Science, Binary Tomography with Deblurring, 4040, 2006

2005

  • Bergtholdt, Martin and Cremers, Daniel and Schnörr, Christoph, Handbook of Mathematical Models in Computer Vision, Paragios, N. and Chen, Y. and Faugeras, O., 147-160, Springer, Variational Segmentation with Shape Priors, 2005
  • Bergtholdt, Martin and Schnörr, Christoph, Pattern Recognition, Proc.~27th DAGM Symposium, 342--350, Springer, LNCS, Shape Priors and Online Appearance Learning for Variational Segmentation and Object Recognition in Static Scenes, 3663, 2005
  • Bruhn, Andrés and Weickert, Joachim and Feddern, Christian and Kohlberger, Timo and Schnörr, Christoph, IEEE Trans.~Image Proc., 608--615, Variational optic flow computation in real-time, 14, 2005
  • Bruhn, Andrés and Weickert, Joachim and Kohlberger, Timo and Schnörr, Christoph, Scale-Space 2005, 279--290, Springer, LNCS, Discontinuity-Preserving Computation of Variational Optic Flow in Real-Time, 3459, 2005
  • Bruhn, Andrés and Weickert, Joachim and Schnörr, Christoph, IJCV, 211-231, Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods, 61, 2005
  • Heiler, M. and Keuchel, J. and Schnörr, C., Pattern Recognition, Proc.~27th DAGM Symposium, 309--317, Springer, LNCS, Semidefinite Clustering for Image Segmentation with A-priori Knowledge, 3663, 2005
  • Heiler, M. and Schnörr, C., Int.~J.~Comp.~Vision, 5--19, Natural Image Statistics for Natural Image Segmentation, 63, 2005
  • Beijing, China, Heiler, M. and Schnörr, C., Proc.~Tenth IEEE Int.~Conf.~Computer Vision (ICCV'05), 1667-1674, Learning Sparse Image Codes by Convex Programming, 2005
  • Heiler, M. and Schnörr, C., Proc.~Int.~Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05), 600-616, Springer, LNCS, Reverse-Convex Programming for Sparse Image Codes, 3757, 2005
  • Kohlberger, T. and Schnörr, C. and Bruhn, A. and Weickert, J., IEEE Trans.~Image Proc., 1125-1137, Domain decomposition for variational optical flow computation, 14, 2005
  • Neumann, J. and Schnörr, C. and Steidl, G., Machine Learning, 129-150, Combined SVM-based Feature Selection and Classification, 61, 2005
  • Neumann, J. and Schnörr, C. and Steidl, G., Pattern Recognition, 1815-1830, Efficient Wavelet Adaption for Hybrid Wavelet-Large Margin Classifiers, 38, 2005
  • Ruhnau, P. and Gütter, C. and Putze, T. and Schnörr, C., Meas.~Science and Techn., 1449-1458, A variational approach for particle tracking velocimetry, 16, 2005
  • Ruhnau, P. and Kohlberger, T. and Nobach, H. and Schnörr, C., Experiments in Fluids, 21--32, pdf, Variational Optical Flow Estimation for Particle Image Velocimetry, 38, 2005
  • Schüle, T. and Schnörr, C. and Weber, S. and Hornegger, J., Discr.~Appl.~Math., 229-243, Discrete Tomography By Convex-Concave Regularization and D.C.~Programming, 151, 2005
  • Schüle, T. and Weber, S. and Schnörr, C., Electr.~Notes in Discr.~Math., 365-384, Adaptive Reconstruction of Discrete-Valued Objects from few Projections, 20, 2005
  • Schellewald, C. and Schnörr, C., Proc.~Int.~Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05), 171-186, Springer, LNCS, Probabilistic Subgraph Matching Based on Convex Relaxation, 3757, 2005
  • Weber, S. and Schüle, T. and Schnörr, C., Electr.~Notes in Discr.~Math., 313-327, Prior Learning and Convex-Concave Regularization of Binary Tomography, 20, 2005
  • Weber, S. and Schnörr, C. and Schüle, T. and Hornegger, J., Geometric Properties from Incomplete Data, Klette, R. and Kozera, R. and Noakes, L. and Weickert, J., Springer, Binary Tomography by Iterating Linear Programs, 2005
  • Welk, Martin and Becker, Florian and Schnörr, Christoph and Weickert, Joachim, Scale-Space 2005, 204--216, Springer, LNCS, Matrix-Valued Filters as Convex Programs, 3459, 2005
  • Yuan, J. and Ruhnau, P. and Mémin, E. and Schnörr, C., Scale-Space 2005, 267--278, Springer, LNCS, Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation, 3459, 2005
  • Yuan, Jing and Schnörr, Christoph and Steidl, Gabriele and Becker, Florian, Proc.~Variational, Geometric and Level Set Methods in Computer Vision, 1--12, Springer, LNCS, A Study of Non-Smooth Convex Flow Decomposition, 3752, 2005
  • Beijing, China, Paragios, N. and Faugeras, O. and Chan, T. and Schnörr, C., Springer, LNCS, Variational, Geometric and Level Sets in Computer Vision (VLSM'05), 3752, 2005

2004

  • Bruhn, Andrés and Jakob, Tobias and Fischer, Markus and Weickert, Joachim and Brüning, Ulrich and Schnörr, Christoph, Real-Time Imaging, 41--51, High performance cluster computing with 3-D nonlinear diffusion filters, 10, 2004
  • Cremers, Daniel and Sochen, Nir and Schnörr, Christoph, Computer Vision -- ECCV 2004, Pajdla, T. and Matas, J., 74-86, Springer, LNCS, Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation, 3024, 2004
  • Giebel, J. and Gavrila, D. M. and Schnörr, C., Computer Vision -- ECCV 2004, Pajdla, T. and Matas, J., 241-252, Springer, LNCS, A Bayesian Framework for Multi-cue 3D Object Tracking, 3024, 2004
  • Keuchel, J. and Heiler, M. and Schnörr, C., Pattern Recognition, Proc.~26th DAGM Symposium, 120-128, Springer, LNCS, Hierarchical Image Segmentation based on Semidefinite Programming, 3175, 2004
  • Kohlberger, T. and Schnörr, C. and Bruhn, A. and Weickert, J., Computer Vision -- ECCV 2004, Pajdla, T. and Matas, J., 205-216, Springer, LNCS, Parallel Variational Motion Estimation by Domain Decomposition and Cluster Computing, 3024, 2004
  • Neumann, J. and Schnörr, C. and Steidl, G., Pattern Recognition, Proc.~26th DAGM Symposium, 212-219, Springer, LNCS, SVM-based Feature Selection by Direct Objective Minimisation, 3175, 2004
  • Karlsruhe, Ruhnau, P. and Kohlberger, T. and Nobach, H. and Schnörr, C., Proc.~Lasermethoden in der Strömungsmeßtechnik, Ruck, B. and Leder, A. and Dopheide, Deutsche Gesellschaft für Laser-Anemometrie GALA e.V., Variational Optical Flow Estimation for Particle Image Velocimetry, 2004
  • Weber, S. and Schüle, T. and Hornegger, J. and Schnörr, C., Combinatorial Image Analysis, Proc.~Int.~Workshop on Combinatorial Image Analysis (IWCIA'04), Klette, R. and \vZuni\'c, J., 38--51, Springer Verlag, LNCS, Binary Tomography by Iterating Linear Programs from Noisy Projections, 3322, 2004
  • Weber, S. and Schüle, T. and Schnörr, C. and Hornegger, J., Methods of Information in Medicine, 320--326, A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections, 43, 2004
  • Cambridge, UK, Yuan, J. and Schnörr, C. and Kohlberger, T. and Ruhnau, P., ICPR 2004 -- 17th Int.~Conf.~on Pattern Recognition, 124-127, IEEE, Convex Set-Based Estimation of Image Flows, 1, 2004

2003

  • Bruhn, Andrés and Weickert, Joachim and Feddern, Christian and Kohlberger, Timo and Schnörr, Christoph, Proc.~Computer Analysis of Images and Patterns (CAIP'03), Petkov, N. and Westenberg, M.A., 222-229, Springer, LNCS, Real-Time Optic Flow Computation with Variational Methods, 2756, 2003
  • Saarland University, Germany, Bruhn, Andrés and Weickert, Joachim and Feddern, Christian and Kohlberger, Timo and Schnörr, Christoph, Variational Optic Flow Computation in Real-Time, 2003
  • Cremers, Daniel and Kohlberger, Timo and Schnörr, Christoph, Pattern Recognition, 1929--1943, pdf, Shape Statistics in Kernel Space for Variational Image Segmentation, 36, 2003
  • Cremers, Daniel and Schnörr, Christoph, Image and Vision Comp., 77-86, Statistical Shape Knowledge in Variational Motion Segmentation, 21, 2003
  • Cremers, Daniel and Sochen, Nir and Schnörr, Christoph, Scale Space Methods in Computer Vision, Griffin, L.D. and Lillholm, M., 388--400, pdf, Springer, LNCS, Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling, 2695, 2003
  • Nice, France, Heiler, M. and Schnörr, C., Proc.~IEEE Int.~Conf.~Computer Vision (ICCV 2003), 1259-1266, Natural Statistics for Natural Image Segmentation, 2003
  • Keuchel, J. and Schnörr, C. and Schellewald, C. and Cremers, D., PAMI, 1364--1379, Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming, 25, 2003
  • Kohlberger, T. and Mémin, E. and Schnörr, C., Scale Space Methods in Computer Vision, Griffin, L.D. and Lillholm, M., 432--448, Springer, LNCS, Variational Dense Motion Estimation Using the Helmholtz Decomposition, 2695, 2003
  • Kohlberger, T. and Schnörr, C. and Bruhn, A. and Weickert, J., Pattern Recognition, Proc.~25th DAGM Symposium, Michaelis, B. and Krell, G., 196--203, Springer, LNCS, Domain Decomposition for Parallel Variational Optical Flow Computation, 2781, 2003
  • University of Mannheim, Germany, Kohlberger, T. and Schnörr, C. and Bruhn, A. and Weickert, J., Domain Decomposition for Variational Optical Flow Computation, 2003
  • Neumann, J. and Schnörr, C. and Steidl, G., Proc.~Computer Analysis of Images and Patterns (CAIP'03), Petkov, N. and Westenberg, M.A., 588--595, Springer, LNCS, Feasible Adaption Criteria for Hybrid Wavelet -- Large Margin Classifiers, 2756, 2003
  • University of Mannheim, Germany, Neumann, J. and Schnörr, C. and Steidl, G., Effectively Finding the Optimal Wavelet for Hybrid Wavelet - Large Margin Signal Classification, 2003
  • University of Mannheim, Germany, Schüle, T. and Schnörr, C. and Weber, S. and Hornegger, J., Discrete Tomography By Convex-Concave Regularization and D.C.~Programming, 2003
  • Palermo, Italy, Schellewald, C. and Schnörr, C., Proc.~Int.~Workshop on Combinatorial Image Analysis (IWCIA'03), Subgraph Matching with Semidefinite Programming, 2003
  • Weber, S. and Schüle, T. and Schnörr, C. and Hornegger, J., Bildverarbeitung für die Medizin 2003, 41--45, Springer Verlag, A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections, 2003
  • Palermo, Italy, Weber, S. and Schnörr, C. and Hornegger, J., Proc.~Int.~Workshop on Combinatorial Image Analysis (IWCIA'03), A Linear Programming Relaxation for Binary Tomography with Smoothness Priors, 2003

2002

  • Zürich, Switzerland, Bruhn, Andrés and Jakob, Tobias and Fischer, Markus and Kohlberger, Timo and Weickert, Joachim and Brüning, Ulrich and Schnörr, Christoph, Pattern Recognition, Proc.~24th DAGM Symposium, van Gool, L., 290--297, Springer, LNCS, Designing 3--D Nonlinear Diffusion Filters for High Performance Cluster Computing, 2449, 2002
  • Zürich, Switzerland, Bruhn, Andrés and Weickert, Joachim and Schnörr, Christoph, Pattern Recognition, Proc.~24th DAGM Symposium, van Gool, L., 454--462, Springer, LNCS, Combining the Advantages of Local and Global Optic Flow Methods, 2449, 2002
  • Cremers, Daniel and Kohlberger, Timo and Schnörr, Christoph, Computer Vision -- ECCV 2002), Heyden, A. and Sparr, G. and Nielsen, M. and Johansen, P., 93--108, pdf, Springer Verlag, LNCS, Nonlinear Shape Statistics in Mumford-Shah Based Segmentation, 2351, 2002
  • Zürich, Switzerland, Cremers, Danial and Schnörr, Christoph, Pattern Recognition, Proc.~24th DAGM Symposium, van Gool, L., 472--480, Springer, LNCS, Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization, 2449, 2002
  • Cremers, Daniel and Tischhäuser, Florian and Weickert, Joachim and Schnörr, Christoph, Int.~J.~Computer Vision, 295--313, Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford--Shah functional, 50, 2002
  • Hinterberger, Walter and Scherzer, Otmar and Schnörr, Christoph and Weickert, Joachim, Numer. Funct. Anal. Optimiz., 69--89, Analysis of Optical Flow Models in the Framework of Calculus of Variations, 23, 2002
  • Keuchel, J. and Naumann, S. and Heiler, M. and Siegmund, A., Remote Sensing of Environment, Automatic Land Cover Analysis for Tenerife by Supervised Classification using Remotely Sensed Data, 2002
  • Zürich, Switzerland, Keuchel, J. and Schnörr, C. and Schellewald, C. and Cremers, D., Pattern Recognition, Proc.~24th DAGM Symposium, van Gool, L., 141--149, Springer, LNCS, Unsupervised Image Partitioning with Semidefinite Programming, 2449, 2002
  • University of Mannheim, Germany, Schellewald, C. and Roth, S. and Schnörr, C., Performance Evaluation of a Convex Relaxation Approach to the Quadratic Assignment of Relational Object Views, 2002

2001

  • Munich, Germany, Cremers, Daniel and Kohlberger, Timo and Schnörr, Christoph, Mustererkennung 2001, Radig, B. and Florczyk, S., 269--276, pdf, Springer, Lect.~Notes Comp.~Science, Nonlinear Shape Statistics via Kernel Spaces, 2191, 2001
  • Vancouver, Canada, Cremers, Daniel and Schnörr, Christoph and Weickert, Joachim, IEEE First Workshop on Variational and Level Set Methods in Computer Vision, 237--244, IEEE Comp.~Soc., Diffusion--Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework, 2001
  • Heers, J. and Schnörr, C. and Stiehl, H.S., IEEE Trans.~Image Proc., 852--864, Globally--Convergent Iterative Numerical Schemes for Non--Linear Variational Image Smoothing and Segmentation on a Multi--Processor Machine, 10, 2001
  • University of Mannheim, Germany, Heiler, M. and Cremers, D. and Schnörr, C., Efficient Feature Subset Selection for Support Vector Machines, 2001
  • Munich, Germany, Keuchel, J. and Schellewald, C. and Cremers, D. and Schnörr, C., Mustererkennung 2001, Radig, B. and Florczyk, S., 353--360, Springer, Lect.~Notes Comp.~Science, Convex Relaxations for Binary Image Partitioning and Perceptual Grouping, 2191, 2001
  • INRIA, Sophia Antipolis, France, Schellewald, C. and Keuchel, J. and Schnörr, C., Proc.~Third Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'01), Figueiredo, M. and Zerubia, J. and Jain, A.K., 267--282, Springer, Lect.~Notes Comp.~Science, Image labeling and grouping by minimizing linear functionals over cones, 2134, 2001
  • Munich, Germany, Schellewald, C. and Roth, S. and Schnörr, C., Mustererkennung 2001, Radig, B. and Florczyk, S., 361--368, Springer, Lect.~Notes Comp.~Science, Evaluation of Convex Optimization Techniques for the Weighted Graph--Matching Problem in Computer Vision, 2191, 2001
  • University of Mannheim, Germany, Schellewald, C. and Roth, S. and Schnörr, C., Application of convex optimization techniques to the relational matching of object views, 2001
  • C.~Schnörr, Statistische Mustererkennung, 2001
  • Weickert, J. and Heers, J. and Schnörr, C. and Zuiderveld, K.--J. and Scherzer, O. and Stiehl, H.--S., Real--Time Imaging, 31--45, Fast parallel algorithms for a broad class of nonlinear variational diffusion approaches, 7, 2001
  • Weickert, J. and Schnörr, C., J.~Math.~Imaging and Vision, 245--255, Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint, 14, 2001
  • Weickert, J. and Schnörr, C., Int.~J.~Computer Vision, 245--264, A Theoretical Framework for Convex Regularizers in PDE--Based Computation of Image Motion, 45, 2001
  • Wiehler, K. and Heers, J. and Schnörr, C. and Stiehl, H.--S. and Grigat, R.--R., Real--Time Imaging, 127--142, A 1D analog VLSI implementation for non-linear real-time signal preprocessing, 7, 2001

2000

  • Berlin, Germany, Cremers, Daniel and Schnörr, Christoph and Weickert, Joachim and Schellewald, Christian, 3rd Workshop on Dynamic Perception, Baratoff, G. and Neumann, H., 117--122, Akad.~Verlagsges., Proc.~in Artificial Intelligence, Learning Translation Invariant Shape Knowledge for Steering Diffusion-Snakes, 9, 2000
  • Kiel, Cremers, Daniel and Schnörr, Christoph and Weickert, Joachim and Schellewald, Christian, Proc.~Algebraic Frames for the Perception-Action Cycle, Sommer, G. and Zeevi, Y., 164--174, Springer, LNCS, Diffusion Snakes Using Statistical Shape Knowledge, 1888, 2000
  • San Diego, Schnörr, C., Computer Vision and Applications: A Guide for Students and Practitioners, Jähne, B. and Haußecker, H., 459--482, Academic Press, Variational Adaptive Smoothing and Segmentation, 2000
  • Kiel, Germany, Schnörr, C. and Weickert, J., Mustererkennung 2000, Sommer, G., Springer, Informatik aktuell, Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives, 2000
  • Weickert, J. and Schnörr, C., Künstliche Intelligenz, 5--10, PDE--Based Preprocessing of Medical Images, 3, 2000
  • Berlin, Germany, Wulf, M. and Stiehl, H.S. and Schnörr, C., Proc.~2nd ICSC Symposium on Neural Computation (NC 2000), Bothe, H. and Rojas, R., On the computational r\^ole of the primate retina, 2000
  • Schnörr, C., Künstliche Intelligenz: Special Issue on Medical Computer Vision, 3, 2000

1999

  • University of Hamburg, Germany, Heers, J. and Schnörr, C. and Stiehl, H.S., Investigating a class of iterative schemes and their parallel implementation for nonlinear variational image smoothing and segmentation, 1999
  • Peckar, W. and Schnörr, C. and Rohr, K. and Stiehl, H.--S., J.~Math.~Imaging and Vision, 143--162, Parameter-Free Elastic Deformation Approach for 2D and 3D Registration Using Prescribed Displacements, 10, 1999
  • San Diego, Schnörr, C., Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition, Jähne, B. and Haußecker, H. and Geißler, P., 451--484, Academic Press, Variational Methods for Adaptive Image Smoothing and Segmentation, 2, 1999
  • Weickert, J. and Schnörr, C., Mustererkennung 1999, Förstner, W. and Buhmann, J.M. and Faber, A. and Faber, P., 317--324, Springer, Informatik aktuell, Räumlich--zeitliche Berechnung des optischen Flusses mit nichtlinearen flussabhängigen Glattheitstermen, 1999
  • Wulf, M. and Stiehl, H.S. and Schnörr, C., Proc.~1st Göttingen Conf.~German Neurosci.~Soc., Elsner, N. and Eysel, U., A model of spatiotemporal receptive fields in the primate retina, II, 1999
  • Bremen, Germany, Wulf, M. and Stiehl, H.S. and Schnörr, C., Proc.~Cognitive Neurosci.~Conf., Modeling spatiotemporal receptive fields in the primate retina, 1999

1998

  • Glasgow, Scotland, Heers, J. and Schnörr, C. and Stiehl, H.S., Proc.~Noblesse Workshop on Non--Linear Model Based Image Analysis (NMBIA'98), A class of parallel algorithms for nonlinear variational image segmentation, 1998
  • Chicago, Heers, J. and Schnörr, C. and Stiehl, H.--S., Proc.~IEEE Int.~Conf.~Image Proc., Investigation of Parallel and Globally Convergent Iterative Schemes for Nonlinear Variational Image Smoothing and Segmentation, 1998
  • Heidelberg, Heers, J. and Schnörr, C. and Stiehl, H.--S., Mustererkennung 1998, Springer, Informatik aktuell, Parallele und global konvergente iterative Minimierung nichtlinearer Variationsansätze zur adaptiven Glättung und Segmentation von Bildern, 1998
  • Southampton/UK, Peckar, W. and Schnörr, C. and Rohr, K. and Stiehl, H.S., 9th British Machine Vision Conference (BMVC`98), Carter, J.N. and Nixon, M.S., 134--143, Non-Rigid Image Registration Using a Parameter-Free Elastic Model, 1998
  • Peckar, W. and Schnörr, C. and Rohr, K. and Stiehl, H.--S. and Spetzger, U., Machine Graphics \& Vision, 807--829, Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements, 7, 1998
  • Hamburg, Germany, Schnörr, C., Variational approaches to Image Segmentation and Feature Extraction, 1998
  • Schnörr, C., J. of Math. Imag. and Vision, 271--292, A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction, 8, 1998
  • London, Wiehler, K. and Grigat, R.--R. and Heers, J. and Schnörr, C. and Stiehl, H.S., Proc.~5th IEEE Int.~Workshop on Cellular Neural Networks and their Applications, Dynamic Circular Cellular Networks for Adaptive Smoothing of Multi--Dimensional Signals, 1998
  • Heidelberg, Wiehler, K. and Grigat, R.--R. and Heers, J. and Schnörr, C. and Stiehl, H.--S., Mustererkennung 1998, Springer, Informatik aktuell, Real--Time Adaptive Smoothing with a 1D Nonlinear Relaxation Network in Analogue VLSI Technology, 1998

1997

  • San Juan, Puerto Rico, Fornland, Pär and Schnörr, Christoph, Proc.~Int.~Conf.~Comp.~Vision and Patt.~Recog.~(CVPR'97), Determining the Dominant Plane from Uncalibrated Stereo Vision by a Robust and Convergent Iterative Approach without Correspondence, 1997
  • Hamburg, Germany, Gerloff, S. and Hagemann, A. and Schnörr, C. and Tieck, S. and Stiehl, H.S. and Dombrowski, R. and Dreyer, M. and Wiesendanger, R., Proc.~9th Int.~Conf.~on Scanning Tunneling Microscopy/Spectroscopy and Related Techniques (STM'97), Semi--Automated Analysis of SXM Images, 1997
  • Florence, Italy, Peckar, W. and Schnörr, C. and Rohr, K. and Stiehl, H.S., Proc.~9th Int.~Conf.~on Image Analysis and Processing (ICIAP'97), Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements, 1997

1996

  • Berlin, Heidelberg, Schnörr, C., Mustererkennung 1996, Jähne, B. and Geißler, P. and Haußecker, H. and Hering, I., 21--28, Springer-Verlag, Informatik aktuell, Repräsentation von Bilddaten mit einem konvexen Variationsansatz, 1996
  • Universität Hamburg, Schnörr, C., Representation of Images by a Convex Variational Diffusion Approach, 1996
  • Schnörr, C. and Sprengel, R. and Neumann, B., Computing Suppl., 149-165, A Variational Approach to the Design of Early Vision Algorithms, 11, 1996
  • Seville, Spain, Schnörr, C. and Stiehl, H.-S. and Grigat, R.-R., Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications, On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals, 1996
  • Paris, Schnörr, C., Proc. 12th Int. Conf. on Analysis and Optimization of Systems: Images, Wavelets and PDE's, Springer-Verlag, Lect. Notes in Control and Information Sciences, Convex Variational Segmentation of Multi-Channel Images, 219, 1996

1995

  • Prague, Czech Republic, Schnörr, C. and Peckar, W., Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95), V. Hlavá\vc, R. \vSára, 122-129, Springer Verlag, Lect. Notes in Comp. Sci., Motion-Based Identification of Deformable Templates, 970, 1995

1994

  • Jerusalem, Israel, Heikkonen, J. and Koikkalainen, P. and Schnörr, C., 12th Int. Conf. on Pattern Recognition, Building Trajectories via Selforganization from Spatiotemporal Features, 1994
  • Schnörr, C., Mustererkennung 1994, Kropatsch, W.G. and Bischof, H., 178--185, Technische Universität Wien, Informatik Xpress, Bewegungssegmentation von Bildfolgen durch die Minimierung konvexer nicht-quadratischer Funktionale, 5, 1994
  • Jerusalem, Israel, Schnörr, C., 12th Int. Conf. on Pattern Recognition, Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals, 1994
  • Schnörr, C., JMIV, 189--198, Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals, 4, 1994
  • Schnörr, C. and Sprengel, R., Biol. Cybernetics, 141--149, A Nonlinear Regularization Approach to Early Vision, 72, 1994
  • Sprengel, R. and Schnörr, C. and Neumann, B., Mustererkennung 1994, Kropatsch, W.G. and Bischof, H., 315--323, Technische Universität Wien, Informatik Xpress, Detection of Visual Data Transitions in Nonlinear Parameter Space, 5, 1994

1993

  • Rohr, Karl and Schnörr, Christoph, IVC, 273--277, An Efficient Approach to the Identification of Characteristic Intensity Variations, 11, 1993
  • Schnörr, C., PAMI, 1074--1079, On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow, 15, 1993
  • Berlin, Schnörr, C. and Niemann, H. and Kopecz, J., Grundlagen und Anwendungen der Künstlichen Intelligenz, 17. Fachtagung für Künstliche Intelligenz, Herzog, O. and Christaller, T. and Schütt, D., 268--274, Springer-Verlag, Architekturkonzepte zur Bildauswertung, 1993
  • Sprengel, R. and Schnörr, C., Mustererkennung 1993, 15. DAGM-Symposium, Pöppl, S.J. and Handels, H., 134--141, Springer Verlag, Nichtlineare Diffusion zur Integration visueller Daten - Anwendung auf Kernspintomogramme, 1993

1992

  • Schnörr, C., IJCV, 153--165, Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization, 8, 1992
  • Dresden, Schnörr, C. and Neumann, B., Mustererkennung 1992, 14. DAGM-Symposium, Fuchs, S. and Hoffmann, R., 411--416, Springer-Verlag, Ein Ansatz zur effizienten und eindeutigen Rekonstruktion stückweise glatter Funktionen, 1992

1991

  • Schnörr, C., Funktionalanalytische Methoden zur Bestimmung von Bewegungsinformation aus TV-Bildfolgen, 1991
  • Schnörr, C., IJCV, 25--38, Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class, 6, 1991

1990

  • Oberkochen-Aalen, Bister, D. and Rohr, K. and Schnörr, C., Mustererkennung 1990, 12. DAGM-Symposium, Großkopf, R.E., 44--51, Springer-Verlag, Informatik-Fachberichte, Automatische Bestimmung der Trajektorien von sich bewegenden Objekten aus einer Grauwertbildfolge, 254, 1990
  • Oxford/UK, Schnörr, C., Proc. British Machine Vision Conference, 109--114, Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization, 1990

1989

  • Hamburg, Schnörr, C., Mustererkennung 1989, 11. DAGM-Symposium, Burkhardt, H. and Höhne, K.H. and Neumann, B., 294--301, Springer-Verlag, Informatik-Fachberichte, Zur Schätzung von Geschwindigkeitsvektorfeldern in Bildfolgen mit einer richtungsabhängigen Glattheitsforderung, 219, 1989