Robert Geirhos
Robert Geirhos
University of Tübingen & International Max Planck Research School for Intelligent Systems (IMPRS-IS)
Verified email at - Homepage
Cited by
Cited by
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
R Geirhos, P Rubisch, C Michaelis, M Bethge, FA Wichmann, W Brendel
International Conference on Learning Representations (ICLR 2019), 2018
Generalisation in humans and deep neural networks
R Geirhos, CR Medina Temme, J Rauber, HH Schütt, M Bethge, ...
Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018
Comparing deep neural networks against humans: object recognition when the signal gets weaker
R Geirhos, DHJ Janssen, HH Schütt, J Rauber, M Bethge, FA Wichmann
arXiv preprint arXiv:1706.06969, 2017
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
C Michaelis, B Mitzkus, R Geirhos, E Rusak, O Bringmann, AS Ecker, ...
Machine Learning for Autonomous Driving Workshop (NeurIPS 2019), 2019
Shortcut Learning in Deep Neural Networks
R Geirhos, JH Jacobsen, C Michaelis, R Zemel, W Brendel, M Bethge, ...
arXiv preprint arXiv:2004.07780, 2020
Methods and measurements to compare men against machines
FA Wichmann, DHJ Janssen, R Geirhos, G Aguilar, HH Schütt, ...
Electronic Imaging 2017 (14), 36-45, 2017
Comparison-Based Framework for Psychophysics: Lab versus Crowdsourcing
S Haghiri, P Rubisch, R Geirhos, F Wichmann, U von Luxburg
arXiv preprint arXiv:1905.07234, 2019
Of human observers and deep neural networks: A detailed psychophysical comparison
R Geirhos, D Jannsen, H Schütt, M Bethge, FA Wichmann
17th Annual Meeting of the Vision Sciences Society (VSS 2017), 806-806, 2017
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
R Geirhos, K Meding, FA Wichmann
arXiv preprint arXiv:2006.16736, 2020
Inducing a human-like shape bias leads to emergent human-level distortion robustness in CNNs
R Geirhos, P Rubisch, J Rauber, CRM Temme, C Michaelis, W Brendel, ...
19th Annual Meeting of the Vision Sciences Society (VSS 2019), 209c-209c, 2019
An Automatized Heider-Simmel Story Generation Tool.
MV Butz, R Geirhos, J Kneissler
37th Annual Meeting of the Cognitive Science Society (CogSci 2015), 2015
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