Visual Perception

Visual perception research focuses on understanding how humans and artificial systems interpret visual information, aiming to bridge the gap between raw sensory input and high-level cognitive understanding. Current research emphasizes evaluating large vision-language models (LVLMs) across multiple levels of perception, from low-level feature extraction to complex semantic reasoning, using benchmarks that assess both accuracy and the presence of hallucinations or biases. These efforts are crucial for improving the reliability and robustness of AI systems in various applications, from autonomous driving to assistive technologies for visually impaired individuals, and for advancing our understanding of human visual cognition.