Including results for Revisiting Deep Image Smoothing and Intrinsic Image Decompositions.
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Jan 11, 2017 · Deep learning based approaches have also been proposed to compute intrinsic image decompositions when granted access to sufficient labeled training data.
While invaluable for many computer vision applications, decomposing a natural image into intrinsic reflectance and shading layers represents a challenging, ...
We propose an image smoothing approximation and intrinsic image decomposition method based on a modified convolutional neural network architecture applied ...
Qingnan Fan, David P. Wipf, Gang Hua, Baoquan Chen: Revisiting Deep Image Smoothing and Intrinsic Image Decomposition. CoRR abs/1701.02965 (2017).
This is the implementation of CVPR 2018 Oral paper "Revisiting Deep Intrinsic Image Decompositions" by Qingnan Fan et al.
Missing: Smoothing | Show results with:Smoothing
... Intrinsic decomposition is a fundamental problem in computer vision and it is an ill-posed problem. Previous arts mainly investigate the priors from images, ...
This work adopts core network structures that universally reflect loose prior knowledge regarding the intrinsic image formation process and can be largely ...
Missing: Smoothing | Show results with:Smoothing
A collection of intrinsic image/video decomposition based on traditional methods and deep learning methods.
We propose a novel deep learning model to leverage the physics-based shading map for the intrinsic image decomposition task.
Revisiting deep intrinsic image decompositions. In Proceedings of the IEEE conference on computer vision and pattern recognition, 2018. 3. [13] DA Forsyth ...