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.

🚀 Conference Pioneer — CVPR 2013
🧭 Keyword Pioneer — geometric detail
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Machine Learning, Mathematics & Optimization