Paraphrasing Magritte's Observation
This work addresses a specific need in vision research for generating stimuli that align with statistical models, but it is incremental as it builds on existing methods and focuses on a narrow application.
The authors tackled the problem of generating cartoon-like images compatible with statistical training used in prior work on human visual system contrast sensitivity, and they presented a method to create such stimuli while clearly distinguishing representation from reality to avoid issues in academic publications.
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.