Deep Shape from a Low Number of Silhouettes

Conference paper

DOI: 10.1007/978-3-319-49409-8_21

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9915)
Cite this paper as:
Di X., Dahyot R., Prasad M. (2016) Deep Shape from a Low Number of Silhouettes. In: Hua G., Jégou H. (eds) Computer Vision – ECCV 2016 Workshops. ECCV 2016. Lecture Notes in Computer Science, vol 9915. Springer, Cham


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.


Deep 3D reconstruction End to end architecture Silhouettes 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Computer Science and StatisticsTrinity College DublinDublinIreland

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