290 citations · 469 across the 35 of their papers we have counts for
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Sampling Based On Natural Image Statistics Improves Local Surrogate Explainers
Ricardo Kleinlein, Alexander Hepburn, Raúl Santos-Rodríguez +1
Many problems in computer vision have recently been tackled using models whose predictions cannot be easily interpreted, most commonly deep neural networks. Surrogate explainers ar…
On the relation between statistical learning and perceptual distances
Alexander Hepburn, Valero Laparra, Raul Santos-Rodriguez +2
It has been demonstrated many times that the behavior of the human visual system is connected to the statistics of natural images. Since machine learning relies on the statistics o…
Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception
Alexander Hepburn, Raul Santos-Rodriguez
Explaining the decisions of models is becoming pervasive in the image processing domain, whether it is by using post-hoc methods or by creating inherently interpretable models. Whi…
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance
Alexander Hepburn, Valero Laparra, Ryan McConville +1
In recent years there has been a growing interest in image generation through deep learning. While an important part of the evaluation of the generated images usually involves visu…