CLC number: TP302
On-line Access: 2024-07-30
Received: 2023-04-30
Revision Accepted: 2024-07-30
Crosschecked: 2023-11-09
Cited: 0
Clicked: 634
Liuqing CHEN, Qianzhi JING, Yixin TSANG, Tingting ZHOU. Iris: a multi-constraint graphic layout generation system[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(7): 968-987.
@article{title="Iris: a multi-constraint graphic layout generation system",
author="Liuqing CHEN, Qianzhi JING, Yixin TSANG, Tingting ZHOU",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="25",
number="7",
pages="968-987",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300312"
}
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%A Liuqing CHEN
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%A Yixin TSANG
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%J Frontiers of Information Technology & Electronic Engineering
%V 25
%N 7
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2300312
TY - JOUR
T1 - Iris: a multi-constraint graphic layout generation system
A1 - Liuqing CHEN
A1 - Qianzhi JING
A1 - Yixin TSANG
A1 - Tingting ZHOU
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 25
IS - 7
SP - 968
EP - 987
%@ 2095-9184
Y1 - 2024
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2300312
Abstract: In graphic design, layout is a result of the interaction between the design elements in the foreground and background images. However, prevalent research focuses on enhancing the quality of layout generation algorithms, overlooking the interaction and controllability that are essential for designers when applying these methods in real-world situations. This paper proposes a user-centered layout design system, Iris, which provides designers with an interactive environment to expedite the workflow, and this environment encompasses the features of user-constraint specification, layout generation, custom editing, and final rendering. To satisfy the multiple constraints specified by designers, we introduce a novel generation model, multi-constraint LayoutVQ-VAE, for advancing layout generation under intra- and inter-domain constraints. Qualitative and quantitative experiments on our proposed model indicate that it outperforms or is comparable to prevalent state-of-the-art models in multiple aspects. User studies on Iris further demonstrate that the system significantly enhances design efficiency while achieving human-like layout designs.
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