2017 Eurographics Intrinsic Decompositions for Image Editing Code Dataset 2017 NeurIPS Self-Supervised Intrinsic Image Decomposition Code / Dataset 2018 CVPR Intrinsic Image Transformation via Scale Space Decom
The shadow map is used for the shading edge calculation. For datasets without such ground truth decompositions, the shadow edges are simu- lated by subtracting the reflectance edges from the shading ground truth edges. Under the Lambertian model, it can be ass...
[5] proposed Intrinsic Images in the Wild, a large scale, public dataset for evaluating intrinsic image decompositions of indoor scenes. Laffont [18,20] proposed the first synthetic dataset that depicts a scene with complex geometry, under multiple physically-based lighting conditions for each view...
We propose a method for generating high-resolution intrinsic image decompositions for in-the-wild images. Our method consists of multiple stages. We first estimate a grayscale shading layer using our ordinal shading pipeline. We then estimate low-resolution chromaticity information to account for color...
For efficiency, we extend Retinex theory, working on the gradient domain, where new albedo and occlusion terms are introduced. Results show that our method provides 4D intrinsic decompositions difficult to achieve with previous state-of-the-art algorithms. We further provide a comprehensive analysis ...
image intrinsic decomposition. While attesttime it is capable of decomposing arbitrarysingleimage. To be more specific, we design a two stream deep architecture that observes a pair of images and aims to explain the variations of the scene by predicting the correct intrinsic decompositions. No ...
Cur matrix decompositions for improved data analysis Proc Natl Acad Sci, 106 (3) (2009), pp. 697-702 CrossrefView in ScopusGoogle Scholar [35] M.D. Ritchie, E.R. Holzinger, R. Li, S.A. Pendergrass, D. Kim Methods of integrating data to uncover genotype–phenotype interactions Nature ...
Intrinsic imaging or intrinsic image decomposition is the problem of decomposing an image into two layers: the reflectance layer, which describes the albedo color of the material; and the illumination or shading layer, which contains information about the interaction between light and geometry. This ...
Revisiting Deep Intrinsic Image Decompositions This is the implementation of CVPR 2018 Oral paper "Revisiting Deep Intrinsic Image Decompositions" by Qingnan Fan et al.. Check my homepage for the paper, supplemental material, slides and the other info. Compilation Our codes are implemented in Torch...
To be more spe- cific, we design a two stream deep architecture that observes a pair of images and aims to explain the variations of the scene by predicting the correct intrinsic decompositions. No ground truth is required for learning. The model reduces to a Unsupervised Single Image ...