Publications by F. Wichmann

Preprints


S. Haghiri, P. Rubisch, R. Geirhos, F. Wichmann, and U. von Luxburg
Comparison-Based Framework for Psychophysics: Lab versus Crowdsourcing
arXiv, 2019
URL, BibTex

Journal Articles


R. Geirhos, J.-H. Jacobsen, C. Michaelis, R. Zemel, W. Brendel, M. Bethge, and F. A. Wichmann
Shortcut Learning in Deep Neural Networks
Nature Machine Intelligence, 2, 665-673, 2020
Code, URL, DOI, BibTex
T. S. A. Wallis, C. M. Funke, A. S. Ecker, L. A. Gatys, F. A. Wichmann, and M. Bethge
Image content is more important than Bouma's Law for scene metamers
ELife, 2019
URL, DOI, BibTex
T. S. A. Wallis, C. M. Funke, A. S. Ecker, L. A. Gatys, F. A. Wichmann, and M. Bethge
A Parametric Texture Model Based on Deep Convolutional Features Closely Matches Texture Appearance for Humans
Journal of Vision, 17(12), 2017
#visual textures, #style transfer, #perceptual image synthesis, #cnns, #psychophysics, #appearance
Code, URL, DOI, Stimuli, Preprint, BibTex
T. S. A. Wallis, S. Tobias, M. Bethge, and F. A. Wichmann
Detecting Distortions of Peripherally Presented Letter Stimuli under Crowded Conditions
Attention, Perception & Psychophysics, 2017
#psychophysics, #letters, #spatial distortions, #crowding
URL, DOI, BibTex
T. S. A. Wallis, M. Bethge, and F. A. Wichmann
Testing models of peripheral encoding using metamerism in an oddity paradigm
Journal of Vision, 16(2), 2016
#psychophysics, #metamers, #crowding, #image appearance, #scene appearance, #blur
Code, URL, DOI, BibTex
H. E. Gerhard, F. A. Wichmann, and M. Bethge
How Sensitive Is the Human Visual System to the Local Statistics of Natural Images?
PLoS Computational Biology, 9(1), 2013
#natural image statistics, #psychophysics
URL, PDF, BibTex
T. Putzeys, M. Bethge, F. A. Wichmann, J. Wagemans, and R. Goris
A New Perceptual Bias Reveals Suboptimal Population Decoding of Sensory Responses
PLoS Computational Biolology, 8(4), 2012
URL, DOI, PDF, BibTex
J. H. Macke and F. A. Wichmann
Estimating predictive stimulus features from psychophysical data: The decision image technique applied to human faces
Journal of Vision, 10(5), 2010
URL, DOI, BibTex

Conference Papers


R. Geirhos, K. Narayanappa, B. Mitzkus, T. Thieringer, M. Bethge, F. A. Wichmann, and W. Brendel
Partial success in closing the gap between human and machine vision
Advances in Neural Information Processing Systems 34, 2021
Code, URL, BibTex
R. Geirhos, K. Narayanappa, B. Mitzkus, M. Bethge, F. A. Wichmann, and W. Brendel
On the surprising similarities between supervised and self-supervised models
Shared Visual Representations in Humans & Machines Workshop, NeurIPS 2020, 2020
URL, BibTex
R. Geirhos, K. Meding, and F. A. Wichmann
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
Advances in Neural Information Processing Systems 33, 2020
Code, URL, BibTex
R. Geirhos, P. Rubisch, C. Michaelis, M. Bethge, F. A. Wichmann, and W. Brendel
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
International Conference on Learning Representations (ICLR), 2019
Code, URL, BibTex
R. Geirhos, C. R. M. Temme, J. Rauber, H. H. Schütt, M. Bethge, and F. A. Wichmann
Generalisation in humans and deep neural networks
Advances in Neural Information Processing Systems 31, 2018
Code, URL, BibTex
F. A. Wichmann, D. H. Janssen, R. Geirhos, G. Aguilar, H. H. Schütt, M. Maertens, and M. Bethge
Methods and measurements to compare men against machines
Electronic Imaging, 2017(14), 36-45, 2017
URL, DOI, BibTex
M. Bethge, T. V. Wiecki, and F. A. Wichmann
The Independent Components of Natural Images are Perceptually Dependent
Proceedings of SPIE Human Vision and Electronic Imaging XII (EI105), 2007
#natural image statistics, #ica, #psychophysics, #perception
PDF, BibTex

Preprint versions of published papers


R. Geirhos, D. H. J. Janssen, H. H. Schütt, J. Rauber, M. Bethge, and F. A. Wichmann
Comparing deep neural networks against humans: object recognition when the signal gets weaker
arXiv (superseded by "Generalisation in humans and deep neural networks"), 170606969, 2017
Code, URL, BibTex

Abstracts


R. Geirhos, J.-H. Jacobsen, C. Michaelis, R. Zemel, W. Brendel, M. Bethge, and F. A. Wichmann
Unintended cue learning: Lessons for deep learning from experimental psychology
Journal of Vision, 20(11), 652, 2020
DOI, BibTex
R. Geirhos, P. Rubisch, J. Rauber, C. R. M. Temme, C. Michaelis, W. Brendel, M. Bethge, and F. A. Wichmann
Inducing a human-like shape bias leads to emergent human-level distortion robustness in CNNs
Journal of Vision, 19(10), 2019
DOI, BibTex
R. Geirhos, D. Janssen, H. Schütt, M. Bethge, and F. Wichmann
Of human observers and deep neural networks: A detailed psychophysical comparison
Journal of Vision, 17(10), 2017
DOI, BibTex
H. E. Gerhard, T. Wiecki, F. Wichmann, and M. Bethge
Perceptual sensitivity to statistical regularities in natural images
The 9th Göttingen Meeting of the German Neuroscience Society, 2011
#natural image statistics, #psychophysics, #perception
URL, PDF, BibTex
University of Tuebingen BCCN CIN MPI