Pub Date : 2024-05-01DOI: 10.1109/MCG.2024.3367422
Peter W S Butcher, Andrea Batch, David Saffo, Blair MacIntyre, Niklas Elmqvist, Panagiotis D Ritsos, Theresa-Marie Rhyne
Native game engines have long been the 3-D development platform of choice for research in mixed and augmented reality. For this reason, they have also been adopted in many immersive visualization and immersive analytics systems and toolkits. However, with the rapid improvements of WebXR and related open technologies, this choice may not always be optimal for future visualization research. In this article, we investigate common assumptions about native game engines versus WebXR and find that while native engines still have an advantage in many areas, WebXR is rapidly catching up and is superior for many immersive analytics applications.
{"title":"Is Native Naïve? Comparing Native Game Engines and WebXR as Immersive Analytics Development Platforms.","authors":"Peter W S Butcher, Andrea Batch, David Saffo, Blair MacIntyre, Niklas Elmqvist, Panagiotis D Ritsos, Theresa-Marie Rhyne","doi":"10.1109/MCG.2024.3367422","DOIUrl":"10.1109/MCG.2024.3367422","url":null,"abstract":"<p><p>Native game engines have long been the 3-D development platform of choice for research in mixed and augmented reality. For this reason, they have also been adopted in many immersive visualization and immersive analytics systems and toolkits. However, with the rapid improvements of WebXR and related open technologies, this choice may not always be optimal for future visualization research. In this article, we investigate common assumptions about native game engines versus WebXR and find that while native engines still have an advantage in many areas, WebXR is rapidly catching up and is superior for many immersive analytics applications.</p>","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"44 3","pages":"91-98"},"PeriodicalIF":1.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141437835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01Epub Date: 2024-06-21DOI: 10.1109/MCG.2024.3360881
Angelos Chatzimparmpas, Kostiantyn Kucher, Andreas Kerren
Visualization for explainable and trustworthy machine learning remains one of the most important and heavily researched fields within information visualization and visual analytics with various application domains, such as medicine, finance, and bioinformatics. After our 2020 state-of-the-art report comprising 200 techniques, we have persistently collected peer-reviewed articles describing visualization techniques, categorized them based on the previously established categorization schema consisting of 119 categories, and provided the resulting collection of 542 techniques in an online survey browser. In this survey article, we present the updated findings of new analyses of this dataset as of fall 2023 and discuss trends, insights, and eight open challenges for using visualizations in machine learning. Our results corroborate the rapidly growing trend of visualization techniques for increasing trust in machine learning models in the past three years, with visualization found to help improve popular model explainability methods and check new deep learning architectures, for instance.
{"title":"Visualization for Trust in Machine Learning Revisited: The State of the Field in 2023.","authors":"Angelos Chatzimparmpas, Kostiantyn Kucher, Andreas Kerren","doi":"10.1109/MCG.2024.3360881","DOIUrl":"10.1109/MCG.2024.3360881","url":null,"abstract":"<p><p>Visualization for explainable and trustworthy machine learning remains one of the most important and heavily researched fields within information visualization and visual analytics with various application domains, such as medicine, finance, and bioinformatics. After our 2020 state-of-the-art report comprising 200 techniques, we have persistently collected peer-reviewed articles describing visualization techniques, categorized them based on the previously established categorization schema consisting of 119 categories, and provided the resulting collection of 542 techniques in an online survey browser. In this survey article, we present the updated findings of new analyses of this dataset as of fall 2023 and discuss trends, insights, and eight open challenges for using visualizations in machine learning. Our results corroborate the rapidly growing trend of visualization techniques for increasing trust in machine learning models in the past three years, with visualization found to help improve popular model explainability methods and check new deep learning architectures, for instance.</p>","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"PP ","pages":"99-113"},"PeriodicalIF":1.7,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139652255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Empirical BRDF model for goniochromatic materials and soft proofing with reflective inks","authors":"Alina Pranovich, Jeppe Revall Frisvad, Sergiy Valyukh, Sasan Gooran, Daniel Nyström","doi":"10.1109/mcg.2024.3391376","DOIUrl":"https://doi.org/10.1109/mcg.2024.3391376","url":null,"abstract":"","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"42 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140628760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-17DOI: 10.1109/mcg.2024.3390121
Shuo Tong, Han Liu, Yuxin He, Chenxiao Du, Wenqing Wang, Runyuan Guo, Jingyun Liu
{"title":"Weakly Supervised Exaggeration Transfer for Caricature Generation With Cross-Modal Knowledge Distillation","authors":"Shuo Tong, Han Liu, Yuxin He, Chenxiao Du, Wenqing Wang, Runyuan Guo, Jingyun Liu","doi":"10.1109/mcg.2024.3390121","DOIUrl":"https://doi.org/10.1109/mcg.2024.3390121","url":null,"abstract":"","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"126 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140610048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-26DOI: 10.1109/mcg.2024.3361733
Benjamin Watson, Josef Spjut, Joohwan Kim, Byungjoo Lee, Mijin Yoo, Peter Shirley, Rulon Raymond
{"title":"Is Less More? Rendering for Esports","authors":"Benjamin Watson, Josef Spjut, Joohwan Kim, Byungjoo Lee, Mijin Yoo, Peter Shirley, Rulon Raymond","doi":"10.1109/mcg.2024.3361733","DOIUrl":"https://doi.org/10.1109/mcg.2024.3361733","url":null,"abstract":"","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"33 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140312325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-25DOI: 10.1109/mcg.2024.3356288
Chi Wing Fu
{"title":"The Test of Time (ToT) Awards","authors":"Chi Wing Fu","doi":"10.1109/mcg.2024.3356288","DOIUrl":"https://doi.org/10.1109/mcg.2024.3356288","url":null,"abstract":"","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"30 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140300019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-25DOI: 10.1109/mcg.2024.3355573
{"title":"IEEE Computer Society Information","authors":"","doi":"10.1109/mcg.2024.3355573","DOIUrl":"https://doi.org/10.1109/mcg.2024.3355573","url":null,"abstract":"","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"1 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140303284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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