Abstract Both Visual Question Answering (VQA) and image captioning are the problems
which involve Computer Vision (CV) and Natural Language Processing (NLP) domains. In …

Visual question answering (VQA) and image captioning require a shared body of general
knowledge connecting language and vision. We present a novel approach to improve VQA …

Visual Question Answering (VQA) is a research topic of significant interest at the intersection
of computer vision and natural language understanding. Recent research indicates that …

Most of existing works in visual question answering (VQA) are dedicated to improving the
performance of answer predictions, while leaving the explanation of answering unexploited …

Abstract In Visual Question Answering (VQA), an attention mechanism has a critical role in
specifying the different objects present in an image or tells the machine where to focus by …

Abstract Visual Question Answering (VQA) is an extremely stimulating and challenging
research area where Computer Vision (CV) and Natural Language Processig (NLP) have …

Abstract Visual Question Answering (VQA) has recently appeared as a hot research area in
the field of computer vision and natural language processing. A VQA model uses both image …

With the rapid development of deep learning models, great improvements have been
achieved in the Visual Question Answering (VQA) field. However, modern VQA models are …

Numerous attempts have been made in the recent past for the task of free-form and open-
ended Visual Question Answering (VQA). Solving VQA problem typically requires …

Paragraph-style image captions describe diverse aspects of an image as opposed to the
more common single-sentence captions that only provide an abstract description of the …