We present a polarization-based approach to perform diffuse-specular separation from a single polarimetric image, acquired using a flexible, practical capture setup. Our key technical insight is that, unlike previous polarization-based separation methods that assume completely unpolarized diffuse reflectance, we use a more general polarimetric model that accounts for partially polarized diffuse reflections. We capture the scene with a polarimetric sensor and produce an initial analytical diffuse-specular separation that we further pass into a deep network trained to refine the separation. We demonstrate that our combination of analytical separation and deep network refinement produces state-of-the-art diffuse-specular separation, which enables image-based appearance editing of dynamic scenes and enhanced appearance estimation.
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Revisiting the driving force inducing phase separation in PEG-phosphate aqueous biphasic systems
Liquid phase separation using aqueous biphasic systems (ABS) is widely used in industrial processes for the extraction, separation and purification of macromolecules. Using water as the single solvent, a wide...
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- Award ID(s):
- 2117246
- PAR ID:
- 10505664
- Publisher / Repository:
- Faraday
- Date Published:
- Journal Name:
- Faraday Discussions
- ISSN:
- 1359-6640
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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