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Learning to predict 3D surfaces of sculptures from single and multiple views

Abstract:

The objective of this work is to reconstruct the 3D surfaces of sculptures from one or more images using a view-dependent representation. To this end, we train a network, SiDeNet, to predict the Silhouette and Depth of the surface given a variable number of images; the silhouette is predicted at a different viewpoint from the inputs (e.g. from the side), while the depth is predicted at the viewpoint of the input images. This has three benefits. First, the network learns a representation of sh...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1007/s11263-018-1124-0

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
Brasenose College
ORCID:
0000-0002-8945-8573
Publisher:
Springer Publisher's website
Journal:
International Journal of Computer Vision Journal website
Publication date:
2018-10-22
Acceptance date:
2018-10-03
DOI:
EISSN:
1573-1405
ISSN:
0920-5691
Pubs id:
pubs:944864
URN:
uri:066e1725-1271-4177-aea7-ea190027d13d
UUID:
uuid:066e1725-1271-4177-aea7-ea190027d13d
Local pid:
pubs:944864

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