SHREC'18 track

2D image-based 3D scene retrieval

Hameed Abdul-Rashid, Juefei Yuan, Bo Li, Yijuan Lu, Song Bai, Xiang Bai, Ngoc Minh Bui, Minh N Do, Trong Le Do, Anh Duc Duong, Xinwei He, Tu Khiem Le, Wenhui Li, Anan Liu, Xiaolong Liu, Khac Tuan Nguyen, Vinh Tiep Nguyen, Weizhi Nie, Van Tu Ninh, Yuting Su & 6 others Vinh Ton-That, Minh Triet Tran, Shu Xiang, Heyu Zhou, Yang Zhou, Zhichao Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

2D scene image-based 3D scene retrieval is a new research topic in the field of 3D object retrieval. Given a 2D scene image, it is to search for relevant 3D scenes from a dataset. It has an intuitive and convenient framework which allows users to learn, search, and utilize the retrieved results for vast related applications, such as automatic 3D content generation for 3D movie, game and animation production, robotic vision, and consumer electronics apps development, and autonomous vehicles. To advance this promising research, we organize this SHREC track and build the first 2D scene image-based 3D scene retrieval benchmark by collecting 2D images from ImageNet and 3D scenes from Google 3D Warehouse. The benchmark contains uniformly classified 10,000 2D scene images and 1,000 3D scene models of ten (10) categories. In this track, seven (7) groups from five countries (China, Chile, USA, UK, and Vietnam) have registered for the track, while due to many challenges involved, only three (3) groups have successfully submitted ten (10) runs of five methods. To have a comprehensive comparison, seven (7) commonly-used retrieval performance metrics have been used to evaluate their retrieval performance. We also suggest several future research directions for this research topic. We wish this publicly available [ARYLL18] benchmark, comparative evaluation results and corresponding evaluation code, will further enrich and boost the research of 2D scene image-based 3D scene retrieval and its applications.

Original languageEnglish (US)
Title of host publicationEG 3DOR 2018 - Eurographics Workshop on 3D Object Retrieval
PublisherEurographics Association
Pages37-44
Number of pages8
ISBN (Electronic)9783038680536
DOIs
StatePublished - Jan 1 2018
Event11th Eurographics Workshop on 3D Object Retrieval, 3DOR 2018 - Delft, Netherlands
Duration: Apr 16 2018 → …

Publication series

NameEurographics Workshop on 3D Object Retrieval, EG 3DOR
Volume2018-April
ISSN (Print)1997-0463
ISSN (Electronic)1997-0471

Conference

Conference11th Eurographics Workshop on 3D Object Retrieval, 3DOR 2018
CountryNetherlands
CityDelft
Period4/16/18 → …

Fingerprint

Consumer electronics
Warehouses
Animation
Application programs
Robotics

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

Cite this

Abdul-Rashid, H., Yuan, J., Li, B., Lu, Y., Bai, S., Bai, X., ... Zhou, Z. (2018). SHREC'18 track: 2D image-based 3D scene retrieval. In EG 3DOR 2018 - Eurographics Workshop on 3D Object Retrieval (pp. 37-44). (Eurographics Workshop on 3D Object Retrieval, EG 3DOR; Vol. 2018-April). Eurographics Association. https://doi.org/10.2312/3dor.20181051

SHREC'18 track : 2D image-based 3D scene retrieval. / Abdul-Rashid, Hameed; Yuan, Juefei; Li, Bo; Lu, Yijuan; Bai, Song; Bai, Xiang; Bui, Ngoc Minh; Do, Minh N; Do, Trong Le; Duong, Anh Duc; He, Xinwei; Le, Tu Khiem; Li, Wenhui; Liu, Anan; Liu, Xiaolong; Nguyen, Khac Tuan; Nguyen, Vinh Tiep; Nie, Weizhi; Ninh, Van Tu; Su, Yuting; Ton-That, Vinh; Tran, Minh Triet; Xiang, Shu; Zhou, Heyu; Zhou, Yang; Zhou, Zhichao.

EG 3DOR 2018 - Eurographics Workshop on 3D Object Retrieval. Eurographics Association, 2018. p. 37-44 (Eurographics Workshop on 3D Object Retrieval, EG 3DOR; Vol. 2018-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abdul-Rashid, H, Yuan, J, Li, B, Lu, Y, Bai, S, Bai, X, Bui, NM, Do, MN, Do, TL, Duong, AD, He, X, Le, TK, Li, W, Liu, A, Liu, X, Nguyen, KT, Nguyen, VT, Nie, W, Ninh, VT, Su, Y, Ton-That, V, Tran, MT, Xiang, S, Zhou, H, Zhou, Y & Zhou, Z 2018, SHREC'18 track: 2D image-based 3D scene retrieval. in EG 3DOR 2018 - Eurographics Workshop on 3D Object Retrieval. Eurographics Workshop on 3D Object Retrieval, EG 3DOR, vol. 2018-April, Eurographics Association, pp. 37-44, 11th Eurographics Workshop on 3D Object Retrieval, 3DOR 2018, Delft, Netherlands, 4/16/18. https://doi.org/10.2312/3dor.20181051
Abdul-Rashid H, Yuan J, Li B, Lu Y, Bai S, Bai X et al. SHREC'18 track: 2D image-based 3D scene retrieval. In EG 3DOR 2018 - Eurographics Workshop on 3D Object Retrieval. Eurographics Association. 2018. p. 37-44. (Eurographics Workshop on 3D Object Retrieval, EG 3DOR). https://doi.org/10.2312/3dor.20181051
Abdul-Rashid, Hameed ; Yuan, Juefei ; Li, Bo ; Lu, Yijuan ; Bai, Song ; Bai, Xiang ; Bui, Ngoc Minh ; Do, Minh N ; Do, Trong Le ; Duong, Anh Duc ; He, Xinwei ; Le, Tu Khiem ; Li, Wenhui ; Liu, Anan ; Liu, Xiaolong ; Nguyen, Khac Tuan ; Nguyen, Vinh Tiep ; Nie, Weizhi ; Ninh, Van Tu ; Su, Yuting ; Ton-That, Vinh ; Tran, Minh Triet ; Xiang, Shu ; Zhou, Heyu ; Zhou, Yang ; Zhou, Zhichao. / SHREC'18 track : 2D image-based 3D scene retrieval. EG 3DOR 2018 - Eurographics Workshop on 3D Object Retrieval. Eurographics Association, 2018. pp. 37-44 (Eurographics Workshop on 3D Object Retrieval, EG 3DOR).
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abstract = "2D scene image-based 3D scene retrieval is a new research topic in the field of 3D object retrieval. Given a 2D scene image, it is to search for relevant 3D scenes from a dataset. It has an intuitive and convenient framework which allows users to learn, search, and utilize the retrieved results for vast related applications, such as automatic 3D content generation for 3D movie, game and animation production, robotic vision, and consumer electronics apps development, and autonomous vehicles. To advance this promising research, we organize this SHREC track and build the first 2D scene image-based 3D scene retrieval benchmark by collecting 2D images from ImageNet and 3D scenes from Google 3D Warehouse. The benchmark contains uniformly classified 10,000 2D scene images and 1,000 3D scene models of ten (10) categories. In this track, seven (7) groups from five countries (China, Chile, USA, UK, and Vietnam) have registered for the track, while due to many challenges involved, only three (3) groups have successfully submitted ten (10) runs of five methods. To have a comprehensive comparison, seven (7) commonly-used retrieval performance metrics have been used to evaluate their retrieval performance. We also suggest several future research directions for this research topic. We wish this publicly available [ARYLL18] benchmark, comparative evaluation results and corresponding evaluation code, will further enrich and boost the research of 2D scene image-based 3D scene retrieval and its applications.",
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AU - Nguyen, Vinh Tiep

AU - Nie, Weizhi

AU - Ninh, Van Tu

AU - Su, Yuting

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