4 code implementations • ICCV 2017 • Mehdi S. M. Sajjadi, Bernhard Schölkopf, Michael Hirsch
Single image super-resolution is the task of inferring a high-resolution image from a single low-resolution input.
1 code implementation • ICCV 2017 • Patrick Wieschollek, Michael Hirsch, Bernhard Schölkopf, Hendrik P. A. Lensch
As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime.
1 code implementation • 31 Jul 2018 • Muhammad Waleed Gondal, Bernhard Schölkopf, Michael Hirsch
Moreover, we show that a texture representation of those deep features better capture the perceptual quality of an image than the original deep features.
1 code implementation • 4 May 2018 • Matthias Bauer, Valentin Volchkov, Michael Hirsch, Bernhard Schölkopf
The modulation transfer function (MTF) is widely used to characterise the performance of optical systems.
no code implementations • 29 Jun 2017 • Waleed M. Gondal, Jan M. Köhler, René Grzeszick, Gernot A. Fink, Michael Hirsch
Although these approaches could help to build trust in the CNNs predictions, they are only slightly shown to work with medical image data which often poses a challenge as the decision for a class relies on different lesion areas scattered around the entire image.
no code implementations • ICCV 2017 • Tae Hyun Kim, Kyoung Mu Lee, Bernhard Schölkopf, Michael Hirsch
We show the superiority of the proposed method in an extensive experimental evaluation.
no code implementations • 27 Mar 2017 • Lei Xiao, Felix Heide, Wolfgang Heidrich, Bernhard Schölkopf, Michael Hirsch
Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency.
no code implementations • 15 Jul 2016 • Patrick Wieschollek, Bernhard Schölkopf, Hendrik P. A. Lensch, Michael Hirsch
We present a neural network model approach for multi-frame blind deconvolution.
no code implementations • 6 Sep 2016 • Mehdi S. M. Sajjadi, Rolf Köhler, Bernhard Schölkopf, Michael Hirsch
Light field photography captures rich structural information that may facilitate a number of traditional image processing and computer vision tasks.
no code implementations • 28 Jun 2014 • Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
We describe a learning-based approach to blind image deconvolution.
no code implementations • 20 Jul 2018 • Eduardo Pérez-Pellitero, Mehdi S. M. Sajjadi, Michael Hirsch, Bernhard Schölkopf
Together with a video discriminator, we also propose additional loss functions to further reinforce temporal consistency in the generated sequences.
no code implementations • ECCV 2018 • Tae Hyun Kim, Mehdi S. M. Sajjadi, Michael Hirsch, Bernhard Scholkopf
State-of-the-art video restoration methods integrate optical flow estimation networks to utilize temporal information.
no code implementations • CVPR 2013 • Stefan Harmeling, Michael Hirsch, Bernhard Scholkopf
We establish a link between Fourier optics and a recent construction from the machine learning community termed the kernel mean map.
no code implementations • CVPR 2017 • Chaochao Lu, Michael Hirsch, Bernhard Scholkopf
We describe a modular framework for video frame prediction.
no code implementations • ICCV 2015 • Michael Hirsch, Bernhard Scholkopf
Even high-quality lenses suffer from optical aberrations, especially when used at full aperture.