Ground truth dataset and baseline evaluations for intrinsic image algorithms
Author(s)Grosse, Roger Baker; Johnson, Micah K.; Adelson, Edward H.; Freeman, William T.
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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.
DepartmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 2009 IEEE 12th International Conference on Computer Vision
Institute of Electrical and Electronics Engineers
Grosse, R. et al. “Ground truth dataset and baseline evaluations for intrinsic image algorithms.” Computer Vision, 2009 IEEE 12th International Conference on. 2009. 2335-2342. © Copyright 2009 IEEE
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INSPEC Accession Number: 11367860