Visual Question Answer

Visual Question Answering (VQA) focuses on enabling computers to answer questions about images or videos, bridging the gap between visual perception and natural language understanding. Current research emphasizes improving the accuracy and robustness of VQA systems, particularly for handling long-form answers, addressing questions from visually impaired users, and extracting information from diverse sources like medical videos and documents. This involves developing sophisticated multimodal models that integrate visual and textual information, often leveraging large language models and contrastive learning techniques to improve performance. The advancements in VQA have significant implications for accessibility, medical diagnosis support, and information retrieval from visual data.