Visual Knowledge in the Big Model Era: Retrospect and Prospect
Wenguan Wang Yi Yang Yunhe Pan
Visual knowledge is a new form of knowledge representation that can
encapsulate visual concepts and their relations in a succinct, comprehensive,
and interpretable manner, with a deep root in cognitive psychology. As the
knowledge about the visual world has been identified as an indispensable
component of human cognition and intelligence, visual knowledge is poised to
have a pivotal role in establishing machine intelligence. With the recent
advance of Artificial Intelligence (AI) techniques, large AI models (or
foundation models) have emerged as a potent tool capable of extracting
versatile patterns from broad data as implicit knowledge, and abstracting them
into an outrageous amount of numeric parameters. To pave the way for creating
visual knowledge empowered AI machines in this coming wave, we present a timely
review that investigates the origins and development of visual knowledge in the
pre-big model era, and accentuates the opportunities and unique role of visual
knowledge in the big model era.