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    Deep Shape from a Low Number of Silhouettes

    Di, Xinhan and Dahyot, Rozenn and Prasad, Mukta (2016) Deep Shape from a Low Number of Silhouettes. Lecture Notes in Computer Science, 9915. ISSN 0302-9743

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    Despite strong progress in the field of 3D reconstruction from multiple views, holes on objects, transparency of objects and textureless scenes, continue to be open challenges. On the other hand, silhouette based reconstruction techniques ease the dependency of 3d reconstruction on image pixels but need a large number of silhouettes to be available from multiple views. In this paper, a novel end to end pipeline is proposed to produce high quality reconstruction from a low number of silhouettes, the core of which is a deep shape reconstruction architecture. Evaluations on ShapeNet [1] show good quality of reconstruction compared with ground truth.

    Item Type: Article
    Additional Information: Computer Vision – ECCV 2016 Workshops. ECCV 2016. Lecture Notes in Computer Science
    Keywords: Deep 3D reconstruction; End to end architecture; Silhouettes;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15258
    Identification Number:
    Depositing User: Rozenn Dahyot
    Date Deposited: 18 Jan 2022 11:46
    Journal or Publication Title: Lecture Notes in Computer Science
    Publisher: Springer Verlag
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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