Human critical eccentricity for peripheral object detection decreases as the number of nearby objects (clutter) increases, consistent with the visual crowding literature. In contrast, the tested DNN object detectors show no strong relationship between clutter and critical eccentricity; their critical eccentricities remain low regardless of the number of nearby objects. This holds even for models trained on COCO-Periph, which should in principle reflect the degrading effect of clutter on the peripheral representation.
Evidence
correlational
Caveat
Clutter is proxied by the number of ground-truth COCO annotations in the image, which does not label all objects in many scenes; the relationship is assessed qualitatively from Figure 6b without a reported correlation coefficient.