====== Ground truth dataset and baseline evaluations for intrinsic image algorithms ======
==== R. Grosse, M.K. Johnson, E.H. Adelson, and W.T. Freeman, ICCV 2009 ====
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===== Abstract =====
The intrinsic image decomposition aims to retrieve "intrinsic" properties of an image, such as shading and reflectance. To make it possible to quantitatively compare different approaches to this problem in realistic settings, we present a ground-truth dataset of intrinsic image decompositions for a variety of real-world objects.  For each object, we separate an image of it into three components: Lambertian shading, reflectance, and specularities. We use our dataset to quantitatively compare several existing algorithms; we hope that this dataset will serve as a means for evaluating future work on intrinsic images.

===== Project page =====
[[http://people.csail.mit.edu/rgrosse/intrinsic/ | Intrinsic images dataset]]


===== Information =====
---- dataentry pubitem ----
title      : Ground truth dataset and baseline evaluations for intrinsic image algorithms
authors    : R. Grosse, M.K. Johnson, E.H. Adelson, and W.T. Freeman
citation   : Proceedings of the International Conference on Computer Vision
shortcite  : ICCV
year       : 2009
created_dt : 2010-06-02
summary_page : publications:iccv2009
keyword_tags : grosse, johnson, adelson, freeman
pdf_url    : http://people.csail.mit.edu/kimo/publications/intrinsic/iccv09-intrinsic.pdf
type       : publication
---