A Simple Model for Intrinsic Image Decomposition with Depth Cues

@article{Chen2013ASM,
  title={A Simple Model for Intrinsic Image Decomposition with Depth Cues},
  author={Qifeng Chen and Vladlen Koltun},
  journal={2013 IEEE International Conference on Computer Vision},
  year={2013},
  pages={241-248}
}
  • Qifeng Chen, V. Koltun
  • Published 1 December 2013
  • Computer Science
  • 2013 IEEE International Conference on Computer Vision
We present a model for intrinsic decomposition of RGB-D images. Our approach analyzes a single RGB-D image and estimates albedo and shading fields that explain the input. To disambiguate the problem, our model estimates a number of components that jointly account for the reconstructed shading. By decomposing the shading field, we can build in assumptions about image formation that help distinguish reflectance variation from shading. These assumptions are expressed as simple nonlocal… 
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163 Citations
Highly Influential Citations
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Background Citations
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Methods Citations
64
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Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression
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The strategy is to learn a convolutional neural network that directly predicts output albedo and shading channels from an input RGB image patch, which outperforms all prior work, including methods that rely on RGB+Depth input.
Intrinsic Scene Properties from a Single RGB-D Image
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References

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