2025/07/02 by Vladislav Ayzenberg, Sukran Bahar Sener, Kylee Novick +1 · 1 voice · 1 citation
Neuroscience · Computer Science · Engineering · #Face Recognition and Perception #Visual Attention and Saliency Detection #CCD and CMOS Imaging Sensors
paper · pdf · doi:10.1126/sciadv.ads6821
By adulthood, humans rapidly identify objects from sparse visual displays and across large disruptions to their appearance. What are the minimal conditions needed to achieve robust recognition abilities and when might these abilities develop? To answer these questions, we investigated the upper limits of children's object recognition abilities. We found that children as young as 3 years successfully identified objects at speeds of 100 milliseconds (both forward and backward masked) under sparse and disrupted viewing conditions. By contrast, a range of computational models implemented with biologically informed properties or optimized for visual recognition did not reach child-level performance. Models only matched children if they received more object examples than children are capable of experiencing. These findings highlight the robustness of the human visual system in the absence of extensive experience and identify important developmental constraints for building biologically plausible machines.