Beyond learnability: understanding human visual development with DNNs.

Abstract

Recently, Orhan and Lake demonstrated the computational plausibility that children can acquire sophisticated visual representations from natural input data without inherent biases, challenging the need for innate constraints in human learning. The findings may also reveal crucial properties of early visual learning and inform theories of human visual development.