R. Grosse, M. K. Johnson, E. H. Adelson, W. T. Freeman. Ground truth dataset and baseline evaluations for intrinsic image algorithms. International Conference on Computer Vision, 2009.
Grosse et al. introduce a dataset for evaluating intrinsic image algorithms consisting of 20 images, each containing a single object on black background. The dataset is available online: cs.toronto.edu/~rgrosse/intrinsic/. In addition, they evaluate several intrinsic image algorithms on this dataset - the python code is also available at the above page. A short script to run explicitly the Retinex-based algorithm can be found at GitHub.
What is your opinion on this article? Let me know your thoughts on Twitter @davidstutz92 or LinkedIn in/davidstutz92.
Grosse et al. introduce a dataset for evaluating intrinsic image algorithms consisting of 20 images, each containing a single object on black background. The dataset is available online: cs.toronto.edu/~rgrosse/intrinsic/. In addition, they evaluate several intrinsic image algorithms on this dataset - the python code is also available at the above page. A short script to run explicitly the Retinex-based algorithm can be found at GitHub.