Fact-based visual question answering

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August undefined, 2024

WebJun 17, 2016 · Fact-/Knowledge-based Visual Question Answering. Compared to classical VQA, fact-based VQA [158] involves an external knowledge base of facts to … WebWe thus extend a conventional visual question answering dataset, which contains image-question-answer triplets, through additional image-question-answer-supporting fact …

Learning to Reason on Tree Structures for Knowledge-Based Visual ...

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] WebFact-based Visual Question Answering (FVQA) requires external knowledge beyond the visible content to answer questions about an image. This ability is challenging but … my clicks cps

arXiv:2009.00145v1 [cs.AI] 31 Aug 2024

Web541 papers with code • 51 benchmarks • 96 datasets. Visual Question Answering (VQA) is a task in computer vision that involves answering questions about an image. The goal … 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 … 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. … office exercises chart

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

FVQA: Fact-based Visual Question Answering - arxiv.org

WebMar 14, 2024 · The experimental results show that the MSG-KRM model is superior to existing methods in terms of overall accuracy score, achieving a score of 43.58, and with … WebOct 12, 2024 · Fvqa: Fact-based visual question answering. IEEE transactions on pattern analysis and machine intelligence, Vol. 40, 10 (2024), 2413--2427. Google Scholar; Peng Wang, Qi Wu, Chunhua Shen, Anton van den Hengel, and Anthony Dick. 2015. Explicit knowledge-based reasoning for visual question answering. arXiv preprint … office exhaust fanWebTowards these ends, we present a new task and a synthetically-generated dataset to do Fact-based Visual Spoken-Question Answering (FVSQA). FVSQA is based on the … myclick rewards

"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 . " - Fact-based visual question answering

Fact-based visual question answering

WebFeb 15, 2024 · Fvqa: Fact-based visual question answering. IEEE Trans. Pattern Anal. Mach. Intell. (2024) M. Narasimhan, A.G. Schwing, Straight to the facts: Learning … WebJun 17, 2016 · Visual Question Answering (VQA) has attracted a lot of attention in both Computer Vision and Natural Language Processing communities, not least because it offers insight into the relationships between two important sources of information. Current datasets, and the models built upon them, have focused on questions which are …

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WebFact-based Visual Question Answering (FVQA) requires external knowledge beyond the visible content to answer questions about an image. This ability 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, which ... 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, …

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 … WebSep 19, 2024 · Here we introduce FVQA (Fact-based VQA), a VQA dataset which requires, and supports, much deeper reasoning. FVQA primarily contains questions that require …

Webintroduced fact-based visual question answering dataset, outperforming competing methods by more than 5%. Keywords: fact based visual question answering, knowledge bases 1 Introduction When answering questions given a context, such as an image, we seamlessly combine the observed content with general knowledge. For autonomous agents 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 ...

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 Language Processing communities, not …

WebJun 17, 2016 · Visual Question Answering (VQA) has attracted a lot of attention in both Computer Vision and Natural Language Processing communities, not least because it … office expense ircWebDec 1, 2024 · To advocate research in this direction, [4] introduces a Knowledge-based Visual Question Answering (KVQA) task, named as ‘Fact-based’ VQA (FVQA), for answering questions by joint analysis of the image and the knowledge base of facts. The typical solutions for FVQA build a fact graph with fact triplets filtered by the visual … office exercises equipments walkingWebDec 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 … office exitoWebNov 5, 2024 · To advocate research in this direction, [5] introduces a Knowledge-based Visual Question Answering (KVQA) task, named as ‘Fact-based’ VQA (FVQA), for answer-ing questions by joint analysis of the image and the knowledge base of facts. The typical solutions for FVQA build a fact graph with fact triplets ﬁltered by the visual office exigencies office exercises for belly fatWebHere we introduce FVQA (Fact-based VQA), a VQA dataset which requires, and supports, much deeper reasoning. FVQA primarily contains questions that require external … office exit fnawWebMar 17, 2024 · Knowledge-based visual question answering requires the ability of associating external knowledge for open-ended cross-modal scene understanding.One limitation of existing solutions is that they capture relevant knowledge from text-only knowledge bases, which merely contain facts expressed by first-order predicates or … office exp