Text VQA

Text Visual Question Answering (Text-VQA) focuses on answering questions about images containing text, requiring models to integrate visual and textual information. Current research emphasizes improving model robustness by incorporating techniques like query-aware segmentation and cross-attention mechanisms within transformer-based architectures, as well as leveraging large language models (LLMs) for enhanced comprehension. This field is significant for advancing multimodal understanding and has practical applications in areas such as document analysis, image captioning, and assistive technologies for visually impaired individuals. The development of large-scale datasets and the exploration of semi-supervised learning approaches are also driving progress.