Identifying an appropriate underlying graph kernel that reflects pairwise similarities is critical
in many recent graph spectral signal restoration schemes, including image denoising …

Point cloud is a collection of 3D coordinates that are discrete geometric samples of an
object's 2D surfaces. Imperfection in the acquisition process means that point clouds are …

Photo-realistic point cloud capture and transmission are the fundamental enablers for
immersive visual communication. The coding process of dynamic point clouds, especially …

Point cloud is a collection of 3D coordinates that are discrete geometric samples of an
object's 2D surfaces. Using a low-cost 3D scanner to acquire data means that point clouds …

A point cloud is an effective 3D geometrical presentation of data paired with different
attributes such as transparency, normal and color of each point. The imperfect acquisition …

Current point cloud denoising (PCD) models optimize single networks, trying to make their
parameters adaptive to each point in a large pool of point clouds. Such a denoising network …

3D dynamic point clouds provide a natural discrete representation of real-world objects or
scenes in motion, with a wide range of applications in immersive telepresence, autonomous …

A point cloud is a representation of a 3D scene as a discrete collection of geometry plus
other attributes such as color, normal, transparency associated with each point. The …

3D point clouds acquired by low-cost sensors are often in lower spatial resolutions than
desired for rendering images on high-resolution displays. In this paper, we propose a fast …

Point cloud (PC)—a collection of discrete geometric samples of a 3D object's surface—is
typically large, which entails expensive subsequent operations. Thus, PC sub-sampling is of …