Combin- ing neural representation and neural symbolic representation can thereby provide more comprehensive understanding of the given image, with not only deep visual information but also high-level and analogical to human understanding symbolic information, which thereby helps generate more accurate captions.
Aug 24, 2021
Empirically, extensive experiments validate the effectiveness of the proposed method. It enables a more comprehensive understanding of the given image by ...
Nov 22, 2019 · Abstract:Image captioning can be improved if the structure of the graphical representations can be formulated with conceptual positional ...
Sep 1, 2022 · In this paper, we proposed a neural-symbolic visual understanding and reasoning framework based on commonsense knowledge enrichment. Deep neural ...
Nov 18, 2020 · Abstract:Neuro-symbolic representations have proved effective in learning structure information in vision and language.
Missing: Neural | Show results with:Neural
Aug 3, 2023 · Abstract: Traditional image captioning models mainly rely on one encoder-decoder architecture to generate one natural sentence for a given ...
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Dec 13, 2023 · The proposed framework includes scene graph-based image captioning [117] as a downstream task of scene graph generation and knowledge enrichment ...
Scene Graph Generation (SGG) is a symbolic image representation approach based on deep neural networks (DNN) that involves predicting objects, their ...
Explored ensemble learning on deep neural networks for image caption ... Neuro-symbolic visual reasoning for multimedia event processing: Overview ...
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