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  LIME: Live Intrinsic Material Estimation

Meka, A., Maximov, M., Zollhöfer, M., Chatterjee, A., Seidel, H.-P., Richardt, C., et al. (2018). LIME: Live Intrinsic Material Estimation. Retrieved from http://arxiv.org/abs/1801.01075.

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Datensatz-Permalink: http://hdl.handle.net/21.11116/0000-0001-40D9-2 Versions-Permalink: http://hdl.handle.net/21.11116/0000-0001-40E7-2
Genre: Forschungspapier
Latex : LIME: {L}ive Intrinsic Material Estimation

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arXiv:1801.01075.pdf (Preprint), 8MB
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File downloaded from arXiv at 2018-05-07 11:27 Spotlight paper in CVPR 2018
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 Urheber:
Meka, Abhimitra1, Autor              
Maximov, Maxim2, Autor              
Zollhöfer, Michael1, Autor              
Chatterjee, Avishek1, Autor              
Seidel, Hans-Peter1, Autor              
Richardt, Christian3, Autor              
Theobalt, Christian1, Autor              
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, escidoc:40047              
2D2 External, escidoc:persistent22              
3External Organizations, escidoc:persistent22              

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Schlagwörter: Computer Science, Computer Vision and Pattern Recognition, cs.CV
 Zusammenfassung: We present the first end to end approach for real time material estimation for general object shapes with uniform material that only requires a single color image as input. In addition to Lambertian surface properties, our approach fully automatically computes the specular albedo, material shininess, and a foreground segmentation. We tackle this challenging and ill posed inverse rendering problem using recent advances in image to image translation techniques based on deep convolutional encoder decoder architectures. The underlying core representations of our approach are specular shading, diffuse shading and mirror images, which allow to learn the effective and accurate separation of diffuse and specular albedo. In addition, we propose a novel highly efficient perceptual rendering loss that mimics real world image formation and obtains intermediate results even during run time. The estimation of material parameters at real time frame rates enables exciting mixed reality applications, such as seamless illumination consistent integration of virtual objects into real world scenes, and virtual material cloning. We demonstrate our approach in a live setup, compare it to the state of the art, and demonstrate its effectiveness through quantitative and qualitative evaluation.

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 Datum: 2018-01-032018-05-042018
 Publikationsstatus: Online publiziert
 Seiten: 17 p.
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: arXiv: 1801.01075
URI: http://arxiv.org/abs/1801.01075
BibTex Citekey: Meka_arXiv1801.01075
 Art des Abschluß: -

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