L. A. Gatys, M. Kümmerer, T. S. A. Wallis, and M. Bethge
Guiding human gaze with convolutional neural networks
arXiv, 2017
#image manipulation, #saliency, #convolutional neural networks
URL, Supplement, 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

M. Kuemmerer, T. Wallis, and M. Bethge
Information-theoretic model comparison unifies saliency metrics
Proceedings of the National Academy of Science, 112(52), 16054-16059, 2015
URL, DOI, BibTex

M. Kümmerer, T. Wallis, and M. Bethge
How close are we to understanding image-based saliency?
arXiv, 2014
#saliency
URL, BibTex

M. Kümmerer, T. S. Wallis, L. A. Gatys, and M. Bethge
Understanding Low- and High-Level Contributions to Fixation Prediction
The IEEE International Conference on Computer Vision (ICCV), 2017
PDF, model webservice, BibTex

M. Kümmerer, T. S. A. Wallis, and M. Bethge
Saliency Benchmarking: Separating Models, Maps and Metrics
arxiv, 2017
URL, BibTex