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    RGB-D to CAD Retrieval with ObjectNN Dataset

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    Date
    2017
    Author
    Hua, Binh-Son
    Truong, Quang-Trung
    Tran, Minh-Khoi
    Pham, Quang-Hieu
    Kanezaki, Asako
    Lee, Tang
    Chiang, HungYueh
    Hsu, Winston
    Li, Bo
    Lu, Yijuan
    Johan, Henry
    Tashiro, Shoki
    Aono, Masaki
    Tran, Minh-Triet
    Pham, Viet-Khoi
    Nguyen, Hai-Dang
    Nguyen, Vinh-Tiep
    Tran, Quang-Thang
    Phan, Thuyen V.
    Truong, Bao
    Do, Minh N.
    Duong, Anh-Duc
    Yu, Lap-Fai
    Nguyen, Duc Thanh
    Yeung, Sai-Kit
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    Abstract
    The goal of this track is to study and evaluate the performance of 3D object retrieval algorithms using RGB-D data. This is inspired from the practical need to pair an object acquired from a consumer-grade depth camera to CAD models available in public datasets on the Internet. To support the study, we propose ObjectNN, a new dataset with well segmented and annotated RGB-D objects from SceneNN [HPN 16] and CAD models from ShapeNet [CFG 15]. The evaluation results show that the RGB-D to CAD retrieval problem, while being challenging to solve due to partial and noisy 3D reconstruction, can be addressed to a good extent using deep learning techniques, particularly, convolutional neural networks trained by multi-view and 3D geometry. The best method in this track scores 82% in accuracy.
    BibTeX
    @inproceedings {3dor.20171048,
    booktitle = {Eurographics Workshop on 3D Object Retrieval},
    editor = {Ioannis Pratikakis and Florent Dupont and Maks Ovsjanikov},
    title = {{RGB-D to CAD Retrieval with ObjectNN Dataset}},
    author = {Hua, Binh-Son and Truong, Quang-Trung and Tran, Minh-Khoi and Pham, Quang-Hieu and Kanezaki, Asako and Lee, Tang and Chiang, HungYueh and Hsu, Winston and Li, Bo and Lu, Yijuan and Johan, Henry and Tashiro, Shoki and Aono, Masaki and Tran, Minh-Triet and Pham, Viet-Khoi and Nguyen, Hai-Dang and Nguyen, Vinh-Tiep and Tran, Quang-Thang and Phan, Thuyen V. and Truong, Bao and Do, Minh N. and Duong, Anh-Duc and Yu, Lap-Fai and Nguyen, Duc Thanh and Yeung, Sai-Kit},
    year = {2017},
    publisher = {The Eurographics Association},
    ISSN = {1997-0471},
    ISBN = {978-3-03868-030-7},
    DOI = {10.2312/3dor.20171048}
    }
    URI
    http://dx.doi.org/10.2312/3dor.20171048
    https://diglib.eg.org:443/handle/10.2312/3dor20171048
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    • 3DOR 17

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    Eurographics Association copyright © 2013 - 2020 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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