Techniques from sparse representation have been successfully applied in many areas like
digital image processing, computer vision and pattern recognition in the past ten years …

The joint bilateral filter is a variant of the standard bilateral filter, where the range kernel is
evaluated using a guidance signal instead of the original signal. It has been successfully …

We present an anisotropic point cloud denoising method using L 0 minimization. The L 0
norm directly measures the sparsity of a solution, and we observe that many common …

We present a data-driven approach for mesh denoising. Our key idea is to formulate the
denoising process with cascaded non-linear regression functions and learn them from a set …

The goal of urban building mesh simplification is to generate a compact representation of a
building from a given mesh. Local smoothness and sharp contours of urban buildings are …

We address the task of single depth image inpainting. Without the corresponding color
images, previous or next frames, depth image inpainting is quite challenging. One natural …

In this article, we present GCN-Denoiser, a novel feature-preserving mesh denoising
method based on graph convolutional networks (GCNs). Unlike previous learning-based …

This article presents a deep normal filtering network, called DNF-Net, for mesh denoising. To
better capture local geometry, our network processes the mesh in terms of local patches …

Many geometry processing applications are sensitive to noise and sharp features. Although
there are a number of works on detecting noise and sharp features in the literature, they are …

Minimizing L 0 gradient, the number of the non-zero gradients of an image, together with a
quadratic data-fidelity to an input image has been recognized as a powerful edge …