WebFeb 17, 2024 · For conducting visual reasoning on all kinds of image–question pairs, in this paper, we propose a novel reasoning model of a question-guided tree structure with a knowledge base (QGTSKB) for ... WebJul 12, 2024 · To bridge these gaps, in this paper, we propose a Zero-shot VQA algorithm using knowledge graphs and a mask-based learning mechanism for better incorporating external knowledge, and present new answer-based Zero-shot VQA splits for the F-VQA dataset. Experiments show that our method can achieve state-of-the-art performance in …
Fact-based visual question answering via dual-process system
WebMar 23, 2024 · Towards these ends, we present a new task and a synthetically-generated dataset to do Fact-based Visual Spoken-Question Answering (FVSQA). FVSQA is … WebDec 1, 2024 · The Visual Question Answering (VQA) task requires the agent to answer a question in natural language according to the visual content in an image, which demands for comprehending and reasoning about both visual and textual information. The typical solutions for VQA are based on the CNN-RNN architecture [8] that coarsely fuses the … buzzy boop at the concert
FVQA: Fact-based Visual Question Answering Papers …
WebWe thus extend a conventional visual question answering dataset, which contains image-question-answer triplets, through additional image-question-answer-supporting fact … WebWe thus extend a conventional visual question answering dataset, which contains image-question-answer triplets, through additional image-question-answer-supporting fact tuples. Each supporting-fact is represented as a structural triplet, such as . WebOct 1, 2024 · Introduction. Visual question answering is a task that was proposed to connect computer vision and natural language processing (NLP), to stimulate research, and push the boundaries of both fields. On the one hand, computer vision studies methods for acquiring, processing, and understanding images. In short, its aim is to teach machines … buzzybooth restaurants