A Survey on Intrinsic Images: Delving Deep into Lambert and Beyond

نویسندگان

چکیده

Intrinsic imaging or intrinsic image decomposition has traditionally been described as the problem of decomposing an into two layers: a reflectance, albedo invariant color material; and shading, produced by interaction between light geometry. Deep learning techniques have broadly applied in recent years to increase accuracy those separations. In this survey, we overview results context well-known data sets relevant metrics used literature, discussing their suitability predict desirable decomposition. Although Lambertian assumption is still foundational basis for many methods, show that there increasing awareness on potential more sophisticated physically-principled components formation process, is, optically accurate material models geometry, complete inverse transport estimations. We classify these methods terms type decomposition, considering priors used, well architecture methodology driving process. also provide insights about future directions research, given advances neural, differentiable rendering techniques.

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ژورنال

عنوان ژورنال: International Journal of Computer Vision

سال: 2022

ISSN: ['0920-5691', '1573-1405']

DOI: https://doi.org/10.1007/s11263-021-01563-8