Publications

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Krolla, B, Diebold, M, Goldlücke, B and Stricker, D (2014). Spherical Light Fields. Proceedings of the British Machine Vision Conference. BMVA Press
Hornáček, M, Fitzgibbon, A and Rother, C (2014). SphereFlow: 6 DoF scene flow from RGB-D pairs. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3526–3533
Vogel, F (2006). Spectroscopic Techniques For Gas-Exchange Measurements. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Lauer, F and Schnörr, C (2009). Spectral Clustering of Linear Subspaces for Motion Segmentation. Proc.~IEEE Int.~Conf.~Computer Vision (ICCV'09)PDF icon Technical Report (1.12 MB)
Lauer, F and Schnörr, C (2009). Spectral Clustering of Linear Subspaces for Motion Segmentation. Proc. IEEE Int. Conf. Computer Vision (ICCV'09). Kyoto, Japan
Lauer, F and Schnörr, C (2009). Spectral Clustering of Linear Subspaces for Motion Segmentation. Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, in press. 678-685
Rahaman, N, Arpit, D, Baratin, A, Draxler, F, Lin, M, Hamprecht, F A, Bengio, Y and Courville, A (2018). On the spectral bias of deep neural networks. arXiv preprint arXiv:1806.08734
Antic, B and Ommer, B (2015). Spatio-temporal Video Parsing for Abnormality Detection. arXiv. abs/1502.06235. http://arxiv.org/abs/1502.06235PDF icon Technical Report (4.61 MB)
Reith, S (2014). Spatio-Temporal Slope Measurement Of Short Wind Waves Under The Influence Of Surface Films At The Heidelberg Aeolotron. Institut für Umweltphysik, Universität Heidelberg, Germany. http://www.ub.uni-heidelberg.de/archiv/17697
Rennebaum, A (2017). Spatio-Temporal Properties Of The Initial Wave Formation Phase At The Aeolotron. Institut für Umweltphysik, Universität Heidelberg, Germany
Antic, B, Büchler, U, Wahl, A - S, Schwab, M E and Ommer, B (2015). Spatiotemporal Parsing of Motor Kinematics for Assessing Stroke Recovery. Medical Image Computing and Computer-Assisted Intervention. SpringerPDF icon Article (2.24 MB)
Peter, S (2015). Spatio-Temporal Motif Deconvolution For Calcium Image Analysis. University of Heidelberg
Schwarz, K (2016). Spatio-Temporal Measurements Of Water-Wave Height And Slope Using Laser-Induced Fluorescence And Splines. Institut für Umweltphysik, Universität Heidelberg, Germany
Rocholz, R and Jähne, B (2010). Spatio-temporal measurements of short wind water waves. EGU General Assembly 2010, Symposium AS2.2. EGU2010-5509
Rocholz, R (2008). Spatiotemporal Measurement of Short Wind-Driven Water Waves. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8897
Jähne, (1993). Spatio-Temporal Image Processing: Theory And Scientific Applications. Springer-Verlag
Garbe, C S, Kondermann, D, Jehle, M and Jähne, B (2009). Spatiotemporal image analysis for flow measurements. Imaging Measurement Methods for Flow Analysis, Results of the DFG Priority Programme 1147 Imaging Measurement Methods for Flow Analysis 2003-2009. Springer. 106 289--305
Herzog, A G, Friedl, F and Jähne, B (2010). Spatio-temporal fluctuations of water-sided gas concentration fields under wind-induced turbulence. 6th Int. Symp. Gas Transfer at Water Surfaces, Kyoto, May 17--21, 2010
Uttenweiler, D, Weber, C, Jähne, B, Fink, R H A and Schaar, H (2003). Spatiotemporal anisotropic diffusion filtering to improve signal-to-noise ratios and object restoration in fluorescence microscopic image sequences.. J Biomed Opt. Ruprecht-Karls-Universität Heidelberg, Institut für Physiologie und Pathophysiologie Medical Biophysics, Im Neuenheimer Feld 326, 69120 Heidelberg, Germany. dietmar.uttenweiler@urz.uni-heidelberg.de. 8 40--47. http://dx.doi.org/10.1117/1.1527627
Schmidt, M (2008). Spatiotemporal Analysis of Range Imagery. IWR, Fakultät für Physik und Astronomie, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8879/
Jehle, M (2006). Spatio-temporal analysis of flows close to water surfaces. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/7060/
Rhemann, C, Rother, C, Kohli, P and Gelautz, M (2010). A spatially varying PSF-based prior for alpha matting. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2149–2156
Klinke, J and Jähne, B (1995). Spatial measurement of short ocean waves during the MBL-ARI West Coast Experiment. IAPSO Proceedings, XXI General Assembly, Honolulu, Hawai, August 1995, PS-10 Spatial Structure of Short Ocean Waves. 390
Kirchner, M (2004). Spatial Extensions To Self-Modeling Curve Resolution. University of Heidelberg
Wagner, T, Leue, C, Wenig, M, Pfeilsticker, K and Platt, U (2001). Spatial and temporal distribution of enhanced boundary layer BrO concentrations measured by the GOME instrument aboard ERS-2. J. Geophys. Res. 106 24225--24235
Jähne, B, Jähne, B and Haußecker, H (1999). Spatial and fourier domain. Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press. 35--66
Wanner, S and Goldlücke, B (2012). Spatial and Angular Variational Superresolution of 4D Light Fields. ECCV 2012. Proceedings, Part 5. Springer. 7576 608-621
Wanner, S and Goldlücke, B (2012). Spatial and Angular Variational Super-Resolution of 4D Light Fields. European Conference on Computer Vision (ECCV)
Petra, S, Schröder, A, Wieneke, B and Schnörr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 294--303PDF icon Technical Report (1014.71 KB)
Petra, S, Schröder, A, Wieneke, B and Schnörr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition – 30th DAGM Symposium. Springer Verlag. 5096 294–303
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166PDF icon Technical Report (866.28 KB)
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166
Diego, F and Hamprecht, F A (2014). Sparse Space-Time Deconvolution for Calcium Image Analysis. NIPS. Proceedings. 64-72. http://papers.nips.cc/paper/5342-sparse-space-time-deconvolution-for-calcium-image-analysisPDF icon Technical Report (5.27 MB)
Rother, C (2011). Sparse Higher Order Functions of Discrete Variables–-Representation and Optimization. research.microsoft.com. 45. http://research.microsoft.com/pubs/147370/RotherKohli-SparseHigherOrder.pdf
Peter, S, Kirschbaum, E, Both, M, Campbell, L A, Harvey, B K, Heins, C, Durstewitz, D, Diego, F and Hamprecht, F A (2017). Sparse convolutional coding for neuronal assembly detection. NIPS, poster

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