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LIME: Live Intrinsic Material Estimation

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons136488

Meka,  Abhimitra
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons136490

Zollhöfer,  Michael
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons211205

Chatterjee,  Avishek
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45610

Theobalt,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

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Fulltext (public)

arXiv:1801.01075.pdf
(Preprint), 8MB

Supplementary Material (public)
There is no public supplementary material available
Citation

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.


Cite as: http://hdl.handle.net/21.11116/0000-0001-40D9-2
Abstract
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.