The goal of the Human-inspired Computer Vision workshop is to link and disseminate parallel findings in the fields of neuroscience, psychology, cognitive science, and computer vision, to inform the development of human-inspired computational models capable of solving visual tasks in a human-like fashion. Recent approaches to computer vision can achieve high performance on many tasks. However, the relationship between machine vision and human vision remains unclear. Investigating such a relationship is timely and important for two reasons: improving machine vision and understanding/enhancing human vision.

Improving machine vision: Insights from psychology, cognitive science, and neuroscience can inform current research on computer vision in a human-like fashion. Such an approach can help identify and tackle gaps between humans and machines, in popular research areas that can be investigated from both perspectives.

Understanding and enhancing human vision: Modeling human vision with inspiration from biology is a hot topic in the context of computational cognitive neuroscience, and it can lead to interpretable computer vision models that serve as useful tools to explain neuroscientific and cognitive observations, and to deepen our understanding of the human brain and developmental mechanisms.

See the Call for Papers