Demonstrates that huamns use scene information to guide search towards likely target sizes, resulting in higher miss rates for mis-scaled targets, which does not occur for object detection DNNs.
A variety of structural and functional differences in the brain are correlated with intelligence.
Provides evidence that human experimentation in physical environments is effective at revealing properties of interest, and learning from observations relies on the learning goals.
Reviews recent work that analyzes the egocentric view of infants, highlighting the connection between the data and internal machinery for statistical learning.
Recent research in intuitive physics, guided by knowledge-based and learning-based approaches, shifts to a probabilistic simulation framework that better explains human intuitive physics predictions compared to earlier heuristic models.
Development of artificial neural networks should leverage the insight that much of animal behavior is innate as a result of wiring rules encoded in the genome, learned through billions of years of evolution.
Provides an overview of a curiosity-driven paradigm and relates the results back to the evolutionary process.
Computer vision models trained on data obtained from head-mounted cameras on children performs better than data from adults.