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Robust Photometric Stereo via Dictionary Learning
We propose a model that applies dictionary learning to regularize and reconstruct the normal vectors from the images under the classic Lambertian reflectance model.
Robust Surface Reconstruction from Gradients via Adaptive Dictionary Regularization
This paper introduces a novel approach to robust surface reconstruction from photometric stereo normal vector maps that is particularly well-suited for reconstructing surfaces from noisy gradients.
Robust Photometric Stereo Using Learned Image and Gradient Dictionaries
Photometric stereo is a method for estimating the normal vectors of an object from images of the object under varying lighting conditions.
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