Graphics Layout



Graphics layout concerns about ways to put input graphics elements together to form a structure, which may be 2D page, 2D/3D object, or 3D scene, depending on the types of input graphics elements. The objective of the layout may be to produce a visually pleasing and/or functionally viable structure, through determining suitable properties for the input graphics elements. These properties may include location, orientation, color, size and shape. In this project, we attempt to develop methods to generate novel layouts. In particular, we are interested in using machine learning and deep learning techniques to learn layout features.


Xufang Pang*, Ying Cao*, Rynson Lau, and Antoni Chan, "Directing User Attention via Visual Flow on Web Designs," ACM Trans. on Graphics (SIGGRAPH Asia 2016), 35(6), Article 240, Dec. 2016.

[paper] [video] [suppl] [models] [dataset]

* indicates joint first authors.

Abstract: We present a novel approach that allows web designers to easily direct user attention via visual flow on web designs. By collecting and analyzing users' eye gaze data on real-world webpages under the task-driven condition, we build two user attention models that characterize user attention patterns between a pair of page components. These models enable a novel web design interaction for designers to easily create a visual flow to guide users' eyes (i.e., direct user attention along a given path) through a web design with minimal effort. In particular, given an existing web design as well as a designer-specified path over a subset of page components, our approach automatically optimizes the web design so that the resulting design can direct users' attention to move along the input path. We have tested our approach on various web designs of different categories. Results show that our approach can effectively guide user attention through the web design according to the designer's high-level specification.


Ying Cao, Rynson Lau, and Antoni Chan, "Look Over Here: Attention-Directing Composition of Manga Elements," ACM Trans. on Graphics (SIGGRAPH 2014), 33(4), Article 94, Aug. 2014.

[paper] [suppl] [video]


Abstract: Picture subjects and text balloons are basic elements in comics, working together to propel the story forward. Japanese comics artists often leverage a carefully designed composition of subjects and balloons (generally referred to as panel elements) to provide a continuous and fluid reading experience. However, such a composition is hard to produce for people without the required experience and knowledge. In this paper, we propose an approach for novices to synthesize a composition of panel elements that can effectively guide the reader's attention to convey the story. Our primary contribution is a probabilistic graphical model that describes the relationships among the artist's guiding path, the panel elements, and the viewer attention, which can be effectively learned from a small set of existing manga pages. We show that the proposed approach can measurably improve the readability, visual appeal, and communication of the story of the resulting pages, as compared to an existing method. We also demonstrate that the proposed approach enables novice users to create higher-quality compositions with less time, compared with commercially available programs.


Zhe Huang, Jiang Wang, Hongbo Fu, and Rynson Lau, "Structured Mechanical Collage," IEEE Trans. on Computer Graphics and Visualization, 20(7):1076-1082, July 2014.

[paper] [video] [more results]


Abstract: We present a method to build 3D structured mechanical collages consisting of numerous elements from the database given artist-designed proxy models. The construction is guided by some graphic design principles, namely unity, variety and contrast. Our results are visually more pleasing than previous works as confirmed by a user study.


Ying Cao, Antoni Chan, and Rynson Lau, "Automatic Stylistic Manga Layout," ACM Trans. on Graphics (SIGGRAPH Asia 2012), 31(6), Article 141, Nov. 2012.

[paper] [video] [more results]


Abstract: Manga layout is a core component in manga production, characterized by its unique styles. However, stylistic manga layouts are difficult for novices to produce as it requires hands-on experience and domain knowledge. In this paper, we propose an approach to automatically generate a stylistic manga layout from a set of input artworks with user-specified semantics, thus allowing less-experienced users to create high-quality manga layouts with minimal efforts. We first introduce three parametric style models that encode the unique stylistic aspects of manga layouts, including layout structure, panel importance, and panel shape. Next, we propose a two-stage approach to generate a manga layout: 1) an initial layout is created that best fits the input artworks and layout structure model, according to a generative probabilistic framework; 2) the layout and artwork geometries are jointly refined using an efficient optimization procedure, resulting in a professional-looking manga layout. Through a user study, we demonstrate that our approach enables novice users to easily and quickly produce higher-quality layouts that exhibit realistic manga styles, when compared to a commercially-available manual layout tool.


Last updated in March 2017.