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Intrinsic images and shape refinement
Xinxin Zuo 02/08/2016
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Intrinsic decomposition
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Related works Priors local gradient (Retinex algorithm)
train classifiers (Recovering Intrinsic Images from a Single Image)
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Related works Priors Non-local priors(A Closed-Form Solution to Retinex with Nonlocal Texture Constraints)
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Related works Priors reflectance sparsity, L1
(Intrinsic Images Decomposition Using a Local and Global Sparse Representation of Reflectance) (An L1 Image Transform for Edge-Preserving Smoothing and Scene- Level Intrinsic decomposition)
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Related works Priors Learning (Color Constancy, Intrinsic Images, and Shape Estimation)
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Related works Other methods Reflectance cluster , user interaction
Texture decomposition CNN (Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression)
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Decomposition with depth cues
Normal cues (A Simple Model for Intrinsic Image Decomposition with Depth Cues)
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Decomposition with depth cues II
Efficient Intrinsic Image Decomposition for RGBD Images
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Decomposition and shape refinement I
Intrinsic Scene Properties from a Single RGB-D Image CVPR13
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Decomposition and shape refinement II
Joint estimation of depth, reflectance and illumination for depth refinement ICCV15 workshop
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Decomposition with multiple images I
Photometric Stereo using Internet Images
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Decomposition with multiple images II
Coherent Intrinsic Images from Photo Collections
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Decomposition with multiple images III
Intrinsic Decomposition of Image Sequences from Local Temporal Variations
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Decomposition with multiple images IV
Estimation of Intrinsic Image Sequences from Image+Depth Video
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Shape refinement using shading
Single RGBD Multi-view environment
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Summary Intrinsic images combined with shape refinement
CNN with physics constraints
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