SimiLay: A Developing Web Page Layout Based Visual Similarity Search Engine

Bozkır, Ahmet Selman; Sezer, Ebru Akçapınar

doi:10.1007/978-3-319-08979-9_35

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Two of them [45,46] Two copy-move forgery detection methods [45,46] can barely expose plagiarism in graphic designs, which means that traditional clone forensics cannot be directly applied to perceptual similarity measurement. Notice that, the spatial pyramid matching method [34] developed for website design failed to perform in this application. This is because it only focuses on the similarity of the website layout structure.…”

Section: Evaluation Resultsmentioning

confidence: 99%

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Similarity Evaluation of Graphic Design Based on Deep Visual Saliency Features

Liu

Huang

et al. 2023

Preprint

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The creativity of an excellent design work generally comes from the inspiration and innovation of its main visual features. The similarity between the main visual elements is the most important indicator for detecting plagiarism of design concepts, which is important to protect cultural heritage and copyright. The purpose of this paper is to develop an efficient similarity evaluation scheme for graphic design. A novel deep visual saliency feature extraction generative adversarial network is proposed to deal with the problem of lack of training examples. It consists of two networks: one predicts visual a saliency feature map from an input image; the other takes the output of the first to distinguish whether a visual saliency feature map is a predicted one or ground truth. Different from traditional saliency generative adversarial networks, a residual refinement module is connected after the encoding and decoding network. Design importance maps generated by professional designers are used to guide the network training. A saliency-based segmentation method is developed to not only locate the optimal layout regions but also notice insignificant regions. Priorities are then assigned to different visual elements. Experimental results show that the proposed model obtains state-of-the-art performance among various similarity measurement methods.

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Section: Evaluation Resultsmentioning

confidence: 99%

“…Garrett and Robinson developed iTrace [33] to explore the possibility of detecting plagiarism in visual works based on image similarity. Bozkr and Sezer [34] tried to evaluate the layout similarity of web pages. Spatial pyramid matching was used to classify web page elements.…”

Section: Similarity Evaluation Of Graphic Designsmentioning

confidence: 99%

Similarity Evaluation of Graphic Design Based on Deep Visual Saliency Features

Liu

Huang

et al. 2023

Preprint

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show abstract

Similarity evaluation of graphic design based on deep visual saliency features

Liu

Yang

et al. 2023

J Supercomput

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The creativity of an excellent design work generally comes from the inspiration and innovation of its main visual features. The similarity among primary visual elements stands as a paramount indicator when it comes to identifying plagiarism in design concepts. This factor carries immense importance, especially in safeguarding cultural heritage and upholding copyright protection. This paper aims to develop an efficient similarity evaluation scheme for graphic design. A novel deep visual saliency feature extraction generative adversarial network is proposed to deal with the problem of lack of training examples. It consists of two networks: One predicts a visual saliency feature map from an input image and the other takes the output of the first to distinguish whether a visual saliency feature map is a predicted one or ground truth. Unlike traditional saliency generative adversarial networks, a residual refinement module is connected after the encoding and decoding network. Design importance maps generated by professional designers are used to guide the network training. A saliency-based segmentation method is developed to locate the optimal layout regions and notice insignificant regions. Priorities are then assigned to different visual elements. Experimental results show the proposed model obtains state-of-the-art performance among various similarity measurement methods.

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