C. M. Funke, J. Borowski, K. Stosio, W. Brendel, T. S. A. Wallis, and M. Bethge
Five Points to Check when Comparing Visual Perception in Humans and Machines
Journal of Vision, 2021
Code, URL, 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

C. M. Funke, P. Vicol, K.-C. Wang, M. Kümmerer, R. Zemel, and M. Bethge
Disentanglement and Generalization Under Correlation Shifts
Conference on Lifelong Learning Agents (CoLLAs), 2022
BibTex

C. M. Funke, L. A. Gatys, A. S. Ecker, and M. Bethge
Synthesising Dynamic Textures using Convolutional Neural Networks
arXiv, 2017
#texture synthesis, #dynamic textures
Code, URL, BibTex

J. Borowski, C. M. Funke, K. Stosio, W. Brendel, T. S. A. Wallis, and M. Bethge
The Notorious Difficulty of Comparing Human and Machine Perception
NeurIPS Workshop: Shared Visual Representations in Human & Machine Intelligence (Best Paper Award), 2019
URL, BibTex

C. M. Funke, J. Borowski, T. Wallis, W. Brendel, A. Ecker, and M. Bethge
Comparing the ability of humans and DNNs to recognise closed contours in cluttered images
Journal of Vision, 18(10), 2018
DOI, BibTex