Learning to detect unseen object classes by between-class attribute transfer CH Lampert, H Nickisch, S Harmeling 2009 IEEE conference on computer vision and pattern recognition, 951-958, 2009 | 2903 | 2009 |
Attribute-based classification for zero-shot visual object categorization CH Lampert, H Nickisch, S Harmeling IEEE transactions on pattern analysis and machine intelligence 36 (3), 453-465, 2013 | 1888 | 2013 |
Image denoising: Can plain neural networks compete with BM3D? HC Burger, CJ Schuler, S Harmeling 2012 IEEE conference on computer vision and pattern recognition, 2392-2399, 2012 | 1593 | 2012 |
How to explain individual classification decisions D Baehrens, T Schroeter, S Harmeling, M Kawanabe, K Hansen, ... The Journal of Machine Learning Research 11, 1803-1831, 2010 | 1310 | 2010 |
Learning to deblur CJ Schuler, M Hirsch, S Harmeling, B Schölkopf IEEE transactions on pattern analysis and machine intelligence 38 (7), 1439-1451, 2015 | 654 | 2015 |
Recording and playback of camera shake: Benchmarking blind deconvolution with a real-world database R Köhler, M Hirsch, B Mohler, B Schölkopf, S Harmeling Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 496 | 2012 |
Fast removal of non-uniform camera shake M Hirsch, CJ Schuler, S Harmeling, B Schölkopf 2011 International Conference on Computer Vision, 463-470, 2011 | 407 | 2011 |
A machine learning approach for non-blind image deconvolution CJ Schuler, H Christopher Burger, S Harmeling, B Scholkopf Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 363 | 2013 |
Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data HH Schütt, S Harmeling, JH Macke, FA Wichmann Vision research 122, 105-123, 2016 | 354 | 2016 |
Efficient filter flow for space-variant multiframe blind deconvolution M Hirsch, S Sra, B Schölkopf, S Harmeling 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 307 | 2010 |
Results of the GREAT08 Challenge: an image analysis competition for cosmological lensing S Bridle, ST Balan, M Bethge, M Gentile, S Harmeling, C Heymans, ... Monthly Notices of the Royal Astronomical Society 405 (3), 2044-2061, 2010 | 240 | 2010 |
A few extreme events dominate global interannual variability in gross primary production J Zscheischler, MD Mahecha, J Von Buttlar, S Harmeling, M Jung, ... Environmental Research Letters 9 (3), 035001, 2014 | 235 | 2014 |
Kernel-based nonlinear blind source separation S Harmeling, A Ziehe, M Kawanabe, KR Müller Neural Computation 15 (5), 1089-1124, 2003 | 195 | 2003 |
Image analysis for cosmology: results from the GREAT10 Galaxy Challenge TD Kitching, ST Balan, S Bridle, N Cantale, F Courbin, T Eifler, M Gentile, ... Monthly Notices of the Royal Astronomical Society 423 (4), 3163-3208, 2012 | 192 | 2012 |
Space-variant single-image blind deconvolution for removing camera shake S Harmeling, H Michael, B Schölkopf Advances in Neural Information Processing Systems 23, 829-837, 2010 | 165 | 2010 |
Mask-specific inpainting with deep neural networks R Köhler, C Schuler, B Schölkopf, S Harmeling Pattern Recognition: 36th German Conference, GCPR 2014, Münster, Germany …, 2014 | 162 | 2014 |
Non-stationary correction of optical aberrations CJ Schuler, M Hirsch, S Harmeling, B Schölkopf 2011 International Conference on Computer Vision, 659-666, 2011 | 130 | 2011 |
From outliers to prototypes: ordering data S Harmeling, G Dornhege, D Tax, F Meinecke, KR Müller Neurocomputing 69 (13-15), 1608-1618, 2006 | 126 | 2006 |
Detection and attribution of large spatiotemporal extreme events in Earth observation data J Zscheischler, MD Mahecha, S Harmeling, M Reichstein Ecological Informatics 15, 66-73, 2013 | 124 | 2013 |
Probabilistic inference for solving (PO) MDPs M Toussaint, S Harmeling, A Storkey Technical Report EDI-INF-RR-0934, School of Informatics, University of Edinburgh, 2006 | 112 | 2006 |