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Fact-based visual question answering

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 https://anna-shem.com

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

FVQA: Fact-Based Visual Question Answering - IEEE Xplore

Category:FVQA 2.0: Introducing Adversarial Samples into Fact-based Visual ...

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Fact-based visual question answering

Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based …

WebJan 1, 2024 · Visual Question Answering (VQA) is a challenging vision-to-language task, which requires answering questions about image contents, e.g., visual objects or image scenes. For example, the questions Q1 and Q2 in Fig. 1 are related to the bridge and the tire appearing in images, respectively. Therefore, many existing VQA methods, such as …

Fact-based visual question answering

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WebOct 23, 2024 · 2024 Papers. [2024] [AAAI] BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection. [ paper] [2024] [AAAI] Lattice CNNs for Matching Based Chinese Question Answering. [ paper] [2024] [AAAI] TallyQA Answering Complex Counting Questions. [ paper] Webtitle={Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering, author={Zhu, Zihao and Yu, Jing and Sun, Yajing and Hu, Yue …

WebMar 19, 2024 · The widely used Fact-based Visual Question Answering (FVQA) dataset contains visually-grounded questions that require information retrieval using common sense knowledge graphs to answer. It has been observed that the original dataset is highly imbalanced and concentrated on a small portion of its associated knowledge graph. We … WebJun 16, 2024 · Fact-based Visual Question Answering (FVQA) requires external knowledge beyond visible content to answer questions about an image, which is challenging but indispensable to achieve general VQA. One limitation of existing FVQA solutions is that they jointly embed all kinds of information without fine-grained selection, …

WebJun 17, 2016 · FVQA: Fact-based Visual Question Answering. Visual Question Answering (VQA) has attracted a lot of attention in both Computer Vision and Natural … WebMay 3, 2015 · We propose the task of free-form and open-ended Visual Question Answering (VQA). Given an image and a natural language question about the image, the task is to provide an accurate natural language answer. Mirroring real-world scenarios, such as helping the visually impaired, both the questions and answers are open-ended. …

WebOct 1, 2024 · Liu et al. [27] proposed a fact-based visual question-answering (FVQA) model, which answers questions based on observed images and external knowledge. The core of their research is to enable ...

WebVideo Question Answering Video Question Answering aims to answer questions asked about the content of a video. Inference You can infer with Visual Question Answering models using the vqa (or visual-question … cet time to hawaii timeWebAbstract. Fact-based visual question answering (FVQA) requires the model to answer questions based on the observed images and external knowledge. cet time to israelWebOct 1, 2024 · 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 how to see. cet time to mexico