Vinoth Pandian Sermuga Pandian, Sarah Suleri, C. Beecks, M. Jarke
{"title":"MetaMorph: AI辅助转换低保真草图到更高的保真度","authors":"Vinoth Pandian Sermuga Pandian, Sarah Suleri, C. Beecks, M. Jarke","doi":"10.1145/3441000.3441030","DOIUrl":null,"url":null,"abstract":"Transforming lo-fi UI sketches to higher-fidelities is an expensive, time-consuming process that requires significant rework. In this paper, we systematically research utilizing AI to assist the transformation of lo-fi sketches to higher fidelities. To provide this assistance, we introduce MetaMorph, an AI tool to detect the constituent UI elements of lo-fi sketches. To train MetaMorph, we collected the UISketch dataset that contains 6,785 hand-drawn sketches of 21 UI elements, 201 hand-drawn lo-fi sketches, and 125,000 synthetically generated lo-fi sketches. MetaMorph provides 63.5% mAP for hand-drawn lo-fi sketches and 82.9% mAP for synthetic lo-fi sketches. Results from ASQ indicate that designers experience an above-average satisfaction level towards ease of task completion (4.9), time taken (5.3), and supporting information (5.3) upon utilizing AI assistance for transforming lo-fi sketches. Their qualitative feedback indicates that they perceive utilizing AI as a novel and useful approach to transform lo-fi sketches into higher fidelities.","PeriodicalId":265398,"journal":{"name":"Proceedings of the 32nd Australian Conference on Human-Computer Interaction","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"MetaMorph: AI Assistance to Transform Lo-Fi Sketches to Higher Fidelities\",\"authors\":\"Vinoth Pandian Sermuga Pandian, Sarah Suleri, C. Beecks, M. Jarke\",\"doi\":\"10.1145/3441000.3441030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Transforming lo-fi UI sketches to higher-fidelities is an expensive, time-consuming process that requires significant rework. In this paper, we systematically research utilizing AI to assist the transformation of lo-fi sketches to higher fidelities. To provide this assistance, we introduce MetaMorph, an AI tool to detect the constituent UI elements of lo-fi sketches. To train MetaMorph, we collected the UISketch dataset that contains 6,785 hand-drawn sketches of 21 UI elements, 201 hand-drawn lo-fi sketches, and 125,000 synthetically generated lo-fi sketches. MetaMorph provides 63.5% mAP for hand-drawn lo-fi sketches and 82.9% mAP for synthetic lo-fi sketches. Results from ASQ indicate that designers experience an above-average satisfaction level towards ease of task completion (4.9), time taken (5.3), and supporting information (5.3) upon utilizing AI assistance for transforming lo-fi sketches. Their qualitative feedback indicates that they perceive utilizing AI as a novel and useful approach to transform lo-fi sketches into higher fidelities.\",\"PeriodicalId\":265398,\"journal\":{\"name\":\"Proceedings of the 32nd Australian Conference on Human-Computer Interaction\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 32nd Australian Conference on Human-Computer Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3441000.3441030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 32nd Australian Conference on Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3441000.3441030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MetaMorph: AI Assistance to Transform Lo-Fi Sketches to Higher Fidelities
Transforming lo-fi UI sketches to higher-fidelities is an expensive, time-consuming process that requires significant rework. In this paper, we systematically research utilizing AI to assist the transformation of lo-fi sketches to higher fidelities. To provide this assistance, we introduce MetaMorph, an AI tool to detect the constituent UI elements of lo-fi sketches. To train MetaMorph, we collected the UISketch dataset that contains 6,785 hand-drawn sketches of 21 UI elements, 201 hand-drawn lo-fi sketches, and 125,000 synthetically generated lo-fi sketches. MetaMorph provides 63.5% mAP for hand-drawn lo-fi sketches and 82.9% mAP for synthetic lo-fi sketches. Results from ASQ indicate that designers experience an above-average satisfaction level towards ease of task completion (4.9), time taken (5.3), and supporting information (5.3) upon utilizing AI assistance for transforming lo-fi sketches. Their qualitative feedback indicates that they perceive utilizing AI as a novel and useful approach to transform lo-fi sketches into higher fidelities.
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