2013
CVPR
CVPR 2013
Non-parametric Filtering for Geometric Detail Extraction and Material Representation
Abstract
Geometric detail is a universal phenomenon in real world objects. It is an important component in object modeling, but not accounted for in current intrinsic image works. In this work, we explore using a non-parametric method to separate geometric detail from intrinsic image components. We further decompose an image as albedo * (coarse-scale shading + shading detail). Our decomposition offers quantitative improvement in albedo recovery and material classification.Our method also enables interesting image editing activities, including bump removal, geometric detail smoothing/enhancement and material transfer.
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Conference Pioneer
— CVPR 2013
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Keyword Pioneer
— geometric detail
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Machine Learning, Mathematics & Optimization