Search Results for author: Michael Hirsch

Found 15 papers, 4 papers with code

The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution

1 code implementation31 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.

General Classification Image Reconstruction +1

Perceptual Video Super Resolution with Enhanced Temporal Consistency

no code implementations20 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.

Image Super-Resolution Video Super-Resolution

Automatic Estimation of Modulation Transfer Functions

1 code implementation4 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.

Learning Blind Motion Deblurring

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.

Deblurring

Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images

no code implementations29 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.

General Classification Image Classification

Discriminative Transfer Learning for General Image Restoration

no code implementations27 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.

Deblurring Demosaicking +2

Depth Estimation Through a Generative Model of Light Field Synthesis

no code implementations6 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.

Depth Estimation

Self-Calibration of Optical Lenses

no code implementations ICCV 2015 Michael Hirsch, Bernhard Scholkopf

Even high-quality lenses suffer from optical aberrations, especially when used at full aperture.

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