Visual Input

Visual input processing is a rapidly evolving field aiming to enable machines to understand and reason with visual information as effectively as humans. Current research focuses on improving the visual comprehension of large language and vision-language models (VLMs) through techniques like active perception, attention mechanisms inspired by human gaze, and multimodal prompt engineering, often employing transformer-based architectures. These advancements are crucial for improving the performance of autonomous systems, assistive technologies for the visually impaired, and applications requiring robust visual reasoning, while also revealing and mitigating biases inherent in these models.