Visual Processing

Visual processing research aims to understand how the brain and artificial systems interpret visual information, focusing on both the biological mechanisms and the development of robust computational models. Current research emphasizes improving the robustness and efficiency of artificial vision systems by incorporating biologically-inspired architectures, such as those mimicking pre-cortical processing and incorporating feedback mechanisms, and by developing novel algorithms like mixture-of-experts models and inductive message passing networks. These advancements have implications for improving object recognition, scene understanding, and visual question answering in both artificial intelligence and our understanding of the human visual system.