Matthias Kümmerer
Matthias Kümmerer
Centre for integrative Neuroscience, University Tuebingen
Verified email at bethgelab.org - Homepage
Title
Cited by
Cited by
Year
Deep gaze i: Boosting saliency prediction with feature maps trained on imagenet
M Kümmerer, L Theis, M Bethge
arXiv preprint arXiv:1411.1045, 2014
3012014
DeepGaze II: Reading fixations from deep features trained on object recognition
M Kümmerer, TSA Wallis, M Bethge
arXiv preprint arXiv:1610.01563, 2016
1532016
Understanding low-and high-level contributions to fixation prediction
M Kummerer, TSA Wallis, LA Gatys, M Bethge
Proceedings of the IEEE International Conference on Computer Vision, 4789-4798, 2017
1322017
Information-theoretic model comparison unifies saliency metrics
M Kümmerer, TSA Wallis, M Bethge
Proceedings of the National Academy of Sciences 112 (52), 16054-16059, 2015
1002015
Saliency benchmarking made easy: Separating models, maps and metrics
M Kummerer, TSA Wallis, M Bethge
Proceedings of the European Conference on Computer Vision (ECCV), 770-787, 2018
322018
Accurate, reliable and fast robustness evaluation
W Brendel, J Rauber, M Kümmerer, I Ustyuzhaninov, M Bethge
Advances in Neural Information Processing Systems, 12861-12871, 2019
132019
How close are we to understanding image-based saliency?
M Kümmerer, T Wallis, M Bethge
arXiv preprint arXiv:1409.7686, 2014
92014
Deepgaze ii: Predicting fixations from deep features over time and tasks
M Kümmerer, T Wallis, M Bethge
Journal of Vision 17 (10), 1147-1147, 2017
72017
Guiding human gaze with convolutional neural networks
LA Gatys, M Kümmerer, TSA Wallis, M Bethge
arXiv preprint arXiv:1712.06492, 2017
62017
Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations
M Pedziwiatr, M Kummerer, TSA Wallis, M Bethge, C Teufel
BioRxiv, 2019
12019
Behavioural evidence for the existence of a spatiotopic free-viewing saliency map
M Kümmerer, TSA Wallis, M Bethge
Journal of Vision 19 (10), 305a-305a, 2019
12019
Extending DeepGaze II: Scanpath prediction from deep features
M Kümmerer, T Wallis, M Bethge
Journal of Vision 18 (10), 371-371, 2018
12018
Deep Gaze I: Boosting Saliency Prediction
M Kümmerer, L Theis, M Bethge
Pdfs. Semanticscholar. org, 0
1
Analyzing task-specific patterns in human scanpaths
M Kümmerer, TSA Wallis, M Bethge
Journal of Vision 20 (11), 1191-1191, 2020
2020
Measuring the Importance of Temporal Features in Video Saliency
M Tangemann, M Kümmerer, TSA Wallis, M Bethge
European Conference on Computer Vision, 667-684, 2020
2020
Meaning maps and deep neural networks are insensitive to meaning when predicting human fixations
MA Pedziwiatr, TSA Wallis, M Kümmerer, C Teufel
Journal of Vision 19 (10), 253c-253c, 2019
2019
Deep Neural Networks and Meaning Maps Are Insensitive to Meaning When Predicting Human Fixations During Natural Scene Viewing
MA Pedziwiatr, TSA Wallis, M Kuemmerer, C Teufel
PERCEPTION 48, 78-78, 2019
2019
How well can we predict where people look in images?
M Kummerer
2019
Probing Neural Decision-Making in Behavioral Models of Scanpath Prediction
M Kuemmerer, T Wallis, M Bethge
PERCEPTION 48, 71-71, 2019
2019
Selecting Maximally-Predictive Deep Features to Explain What Drives Fixations in Free-Viewing
M Kümmerer, TSA Wallis, M Bethge
2019
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