Abstract Intrinsic Image Decomposition (IID) is a challenging and interesting computer vision
problem with various applications in several fields. We present novel semantic priors and an
integrated approach for single image IID that involves analyzing image at three hierarchical
context levels. Local context priors capture scene properties at each pixel within a small
neighborhood. Mid-level context priors encode object level semantics. Global context priors
establish correspondences at the scene level. Our semantic priors are designed on both …