ViTextVQA: A Large-Scale Visual Question Answering Dataset and a Novel Multimodal Feature Fusion Method for Vietnamese Text Comprehension in Images

Understand

Visual Question Answering (VQA) is a challenging task that requires the joint understanding of natural language and visual content.

• While early research primarily focused on recognizing objects and scene context, it often overlooked scene text-an essential source of explicit semantic information.
• This paper introduces \textbf{ViTextVQA} (\textbf{Vi}etnamese \textbf{Text}-based \textbf{V}isual \textbf{Q}uestion \textbf{A}nswering), the first large-scale Vietnamese dataset specializing in text-based VQA.
• The dataset contains \textbf{over 16,000} images and \textbf{over 50,000} question-answer pairs.