Visual Data

Visual data analysis is a rapidly evolving field focused on efficiently extracting meaningful information from images and videos, addressing challenges like bias, uncertainty, and efficient annotation. Current research emphasizes developing robust models, including diffusion models and large language models (LLMs), to improve visual data interpretation, particularly for tasks such as image generation, classification, and understanding visualizations. This work is crucial for advancing various applications, from medical image analysis and autonomous driving to enhancing the accessibility of scientific data and improving the safety and fairness of AI systems.