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
Sep 1, 2021 · Empirically, extensive experiments validate the effectiveness of the proposed method. It enables a more comprehensive understanding of the given ...
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Nov 18, 2020 · Abstract:Neuro-symbolic representations have proved effective in learning structure information in vision and language.
Missing: Neural | Show results with:Neural
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 ...
Dec 13, 2023 · The proposed framework includes scene graph-based image captioning [117] as a downstream task of scene graph generation and knowledge enrichment ...
Their work explores techniques for learning meaningful representations of images and sentences, facilitating better alignment between visual and textual ...
The paper focuses on techniques such as Inception V3, Convolutional Neural Network and training deep learning models for captioning images. Provided a training ...
Image captioning is an example of deep learning on mixed data modalities (texts and images). The model input is an image, and the model output is some caption ...
Sep 2, 2015 · It would be a great way to relate how relevant an image and caption are to each other. For a batch of images and captions, we can use the model ...