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dc.contributor.authorYuan, Juefeien_US
dc.contributor.authorLi, Boen_US
dc.contributor.authorLu, Yijuanen_US
dc.contributor.authorBai, Songen_US
dc.contributor.authorBai, Xiangen_US
dc.contributor.authorBui, Ngoc-Minhen_US
dc.contributor.authorDo, Minh N.en_US
dc.contributor.authorDo, Trong-Leen_US
dc.contributor.authorDuong, Anh-Ducen_US
dc.contributor.authorHe, Xinweien_US
dc.contributor.authorLe, Tu-Khiemen_US
dc.contributor.authorLi, Wenhuien_US
dc.contributor.authorLiu, Ananen_US
dc.contributor.authorLiu, Xiaolongen_US
dc.contributor.authorNguyen, Khac-Tuanen_US
dc.contributor.authorNguyen, Vinh-Tiepen_US
dc.contributor.authorNie, Weizhien_US
dc.contributor.authorNinh, Van-Tuen_US
dc.contributor.authorSu, Yutingen_US
dc.contributor.authorTon-That, Vinhen_US
dc.contributor.authorTran, Minh-Trieten_US
dc.contributor.authorXiang, Shuen_US
dc.contributor.authorZhou, Heyuen_US
dc.contributor.authorZhou, Yangen_US
dc.contributor.authorZhou, Zhichaoen_US
dc.contributor.editorTelea, Alex and Theoharis, Theoharis and Veltkamp, Remcoen_US
dc.date.accessioned2018-04-14T18:28:39Z
dc.date.available2018-04-14T18:28:39Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-053-6
dc.identifier.issn1997-0471
dc.identifier.urihttp://dx.doi.org/10.2312/3dor.20181050
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/3dor20181050
dc.description.abstractSketch-based 3D model retrieval has the intuitiveness advantage over other types of retrieval schemes. Currently, there is a lot of research in sketch-based 3D model retrieval, which usually targets the problem of retrieving a list of candidate 3D models using a single sketch as input. 2D scene sketch-based 3D scene retrieval is a brand new research topic in the field of 3D object retrieval. Unlike traditional sketch-based 3D model retrieval which ideally assumes that a query sketch contains only a single object, this is a new 3D model retrieval topic within the context of a 2D scene sketch which contains several objects that may overlap with each other and thus be occluded and also have relative location configurations. It is challenging due to the semantic gap existing between the iconic 2D representation of sketches and more accurate 3D representation of 3D models. But it also has vast applications such as 3D scene reconstruction, autonomous driving cars, 3D geometry video retrieval, and 3D AR/VR Entertainment. Therefore, this research topic deserves our further exploration. To promote this interesting research, we organize this SHREC track and build the first 2D scene sketch-based 3D scene retrieval benchmark by collecting 3D scenes from Google 3D Warehouse and utilizing our previously proposed 2D scene sketch dataset Scene250. The objective of this track is to evaluate the performance of different 2D scene sketch-based 3D scene retrieval algorithms using a 2D sketch query dataset and a 3D Warehouse model dataset. The benchmark contains 250 scene sketches and 1000 3D scene models, and both are equally classified into 10 classes. In this track, six groups from five countries (China, Chile, USA, UK, and Vietnam) have registered for the track, while due to many challenges involved, only 3 groups have successfully submitted 8 runs. The retrieval performance of submitted results has been evaluated using 7 commonly used retrieval performance metrics. We also conduct a thorough analysis and discussion on those methods, and suggest several future research directions to tackle this research problem. We wish this publicly available [YLL18] benchmark, comparative evaluation results and corresponding evaluation code, will further enrich and advance the research of 2D scene sketch-based 3D scene retrieval and its applications.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectH.3.3 [Computer Graphics]
dc.subjectInformation Systems
dc.subjectInformation Search and Retrieval
dc.title2D Scene Sketch-Based 3D Scene Retrievalen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrieval
dc.description.sectionheadersSHREC Tracks
dc.identifier.doi10.2312/3dor.20181050
dc.identifier.pages29-36


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