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.
Roger Grosse, Micah K. Johnson, Edward H. Adelson,