Data-Driven BxDF Models for Computer Vision Applications
ICCV Workshop, October 23rd 2017
Data-Driven BxDF Models for Computer Vision Applications
ICCV Workshop, October 23rd 2017
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Call for Papers
Share your research on applications of data-driven BxDF models in Computer Vision and participate in ICCV 2017!
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Invited Speakers
Listen to invited talks from some of the pioneers within the field, Paul Debevec and Manmohan Chandraker!
Welcome
A key challenge in computer vision is to infer object appearance, which is a combination of geometric shape and radiometric properties. Acquisition of geometric shape has been researched extensively over decades, and we have reached a point where several commercial solutions are available for scanning 3D geometry. With systems available for acquiring shape, the next natural step is to acquire radiometric properties from observing light-material interaction. A particular challenge in this endeavor is the decoupling of incident illumination and intrinsic material properties. This decoupling is necessary for inferring material properties and for simulating object appearance in an arbitrary illumination environment.
The topics to be covered in our workshop will be centered around methods for formulating, capturing, validating, compressing, and applying data-driven BxDF models, and especially their use within the field of computer vision.
Date: October 23rd, 2017
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