Paraphrasing Magritte's Observation

TL;DR

This paper introduces a method to generate cartoon-like images that challenge traditional contrast sensitivity explanations in human vision, emphasizing the distinction between stimulus representation and reality.

Contribution

It presents a novel technique for creating stimuli that align with specific statistical training, inspired by Magritte's paradox, to test visual system theories.

Findings

Generated stimuli are statistically compatible with training data.

The method emphasizes the distinction between representation and reality.

Stimuli challenge existing contrast sensitivity explanations.

Abstract

Contrast Sensitivity of the human visual system can be explained from certain low-level vision tasks (like retinal noise and optical blur removal), but not from others (like chromatic adaptation or pure reconstruction after simple bottlenecks). This conclusion still holds even under substantial change in stimulus statistics, as for instance considering cartoon-like images as opposed to natural images (Li et al. Journal of Vision, 2022, Preprint arXiv:2103.00481). In this note we present a method to generate original cartoon-like images compatible with the statistical training used in (Li et al., 2022). Following the classical observation in (Magritte, 1929), the stimuli generated by the proposed method certainly are not what they represent: Ceci n'est pas une pipe. The clear distinction between representation (the stimuli generated by the proposed method) and reality (the actual object) avoids eventual problems for the use of the generated stimuli in academic, non-profit, publications.