Image Analysis Using Multigrid Relaxation Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from shading
A novel algorithm for color constancy
International Journal of Computer Vision
A physical approach to color image understanding
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color by Correlation: A Simple, Unifying Framework for Color Constancy
IEEE Transactions on Pattern Analysis and Machine Intelligence
SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW
SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW
Recovering Intrinsic Images from a Single Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time edge-aware image processing with the bilateral grid
ACM SIGGRAPH 2007 papers
Entropy Minimization for Shadow Removal
International Journal of Computer Vision
Generalized Gamut Mapping using Image Derivative Structures for Color Constancy
International Journal of Computer Vision
Color lines: image specific color representation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
High-frequency shape and albedo from shading using natural image statistics
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Shape estimation in natural illumination
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Shape, albedo, and illumination from a single image of an unknown object
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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We present SIRFS (shape, illumination, and reflectance from shading), the first unified model for recovering shape, chromatic illumination, and reflectance from a single image. Our model is an extension of our previous work [1], which addressed the achromatic version of this problem. Dealing with color requires a modified problem formulation, novel priors on reflectance and illumination, and a new optimization scheme for dealing with the resulting inference problem. Our approach outperforms all previously published algorithms for intrinsic image decomposition and shape-from-shading on the MIT intrinsic images dataset [1, 2] and on our own "naturally" illuminated version of that dataset.