27 citations · 110 across the 41 of their papers we have counts for
4 papers · 1 filter
Simulating Human Gaze with Neural Visual Attention
Leo Schwinn, Doina Precup, Bjoern Eskofier +1
Existing models of human visual attention are generally unable to incorporate direct task guidance and therefore cannot model an intent or goal when exploring a scene. To integrate…
Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks
Thomas Altstidl, An Nguyen, Leo Schwinn +4
The widespread success of convolutional neural networks may largely be attributed to their intrinsic property of translation equivariance. However, convolutions are not equivariant…
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification
Leo Schwinn, Leon Bungert, An Nguyen +5
The reliability of neural networks is essential for their use in safety-critical applications. Existing approaches generally aim at improving the robustness of neural networks to e…
Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention
Leo Schwinn, Doina Precup, Björn Eskofier +1
By and large, existing computational models of visual attention tacitly assume perfect vision and full access to the stimulus and thereby deviate from foveated biological vision. M…