Object Perception

Object perception research aims to understand how systems, both biological and artificial, identify, categorize, and locate objects within visual scenes. Current efforts focus on improving the robustness and generalization of object perception models, particularly in handling diverse data distributions and complex scenarios, often employing large language models and object-centric learning approaches. These advancements are crucial for improving the performance of robots, autonomous vehicles, and other AI systems that rely on accurate and reliable object understanding, as well as furthering our understanding of human visual cognition.