GUIGAN: Learning to Generate GUI Designs Using Generative Adversarial NetworksTechnical Track
Thu 27 May 2021 01:15 - 01:35 at Blended Sessions Room 3 - 2.2.3. GUI Design
Graphical User Interface (GUI) is ubiquitous in almost all modern desktop software, mobile applications and online websites. A good GUI design is crucial to the success of the software in the market, but designing a good GUI which requires much innovation and creativity is difficult even to well-trained designers. In addition, the requirement of rapid development of GUI design also aggravates designers’ working load. So, the availability of various automated generated GUIs can help enhance the design personalization and specialization as they can cater to the taste of different designers. To assist designers, we develop a model \tool to automatically generate GUI designs. Different from conventional image generation models based on image pixels, our \tool is to reuse GUI components collected from existing mobile app GUIs for composing a new design which is similar to natural-language generation. Our \tool is based on SeqGAN by modelling the GUI component style compatibility and GUI structure. The evaluation demonstrates that our model significantly outperforms the best of the baseline methods by 30.77% in Fr'echet Inception distance (FID) and 12.35% in 1-Nearest Neighbor Accuracy (1-NNA). Through a pilot user study, we provide initial evidence of the usefulness of our approach for generating acceptable brand new GUI designs.
Wed 26 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
12:55 - 13:55 | 2.2.3. GUI DesignTechnical Track / Journal-First Papers at Blended Sessions Room 3 +12h Chair(s): Ignacio Panach Universidad de Valencia | ||
12:55 20mPaper | Wireframe-based UI Design Search through Image AutoencoderJournal-First Journal-First Papers Jieshan Chen Australian National University, Australia, Chunyang Chen Monash University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Liming Zhu Data61 at CSIRO, Australia / UNSW, Australia, John Grundy Monash University, Jinshui Wang Fujian University of Technology Pre-print Media Attached | ||
13:15 20mPaper | GUIGAN: Learning to Generate GUI Designs Using Generative Adversarial NetworksTechnical Track Technical Track Tianming Zhao Jilin University, Chunyang Chen Monash University, Yuanning Liu Jilin University, Xiaodong Zhu Jilin University Pre-print Media Attached | ||
13:35 20mPaper | Don't Do That! Hunting Down Visual Design Smells in Complex UIs against Design GuidelinesTechnical Track Technical Track Bo Yang Zhejiang University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Chunyang Chen Monash University, Deheng Ye Tencent AI Lab, Shanping Li Zhejiang University Pre-print Media Attached |
Thu 27 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
00:55 - 01:55 | |||
00:55 20mPaper | Wireframe-based UI Design Search through Image AutoencoderJournal-First Journal-First Papers Jieshan Chen Australian National University, Australia, Chunyang Chen Monash University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Liming Zhu Data61 at CSIRO, Australia / UNSW, Australia, John Grundy Monash University, Jinshui Wang Fujian University of Technology Pre-print Media Attached | ||
01:15 20mPaper | GUIGAN: Learning to Generate GUI Designs Using Generative Adversarial NetworksTechnical Track Technical Track Tianming Zhao Jilin University, Chunyang Chen Monash University, Yuanning Liu Jilin University, Xiaodong Zhu Jilin University Pre-print Media Attached | ||
01:35 20mPaper | Don't Do That! Hunting Down Visual Design Smells in Complex UIs against Design GuidelinesTechnical Track Technical Track Bo Yang Zhejiang University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Chunyang Chen Monash University, Deheng Ye Tencent AI Lab, Shanping Li Zhejiang University Pre-print Media Attached |