In this paper we present ADOP, a novel point-based, differentiable neural rendering
pipeline. Like other neural renderers, our system takes as input calibrated camera images …

This thesis introduces Potree, a web-based renderer for large point clouds. It allows users to
view data sets with billions of points, from sources such as LIDAR or photogrammetry, in real …

In this paper, we present several compute‐based point cloud rendering approaches that
outperform the hardware pipeline by up to an order of magnitude and achieve significantly …

With better and faster acquisition devices comes a demand for fast robust reconstruction
algorithms, but no L1-based technique has been fast enough for online use so far. In this …

The accelerated collection of detailed real-world 3D data in the form of ever-larger point
clouds is sparking a demand for novel visualization techniques that are capable of rendering …

With the development of 3D measurement systems, dense colored point clouds are
increasingly available. However, up to now, their use in interactive applications has been …

Abstract 3D point clouds represent an essential category of geodata used in a variety of
geoinformation applications and systems. We present a novel, interactive out-of-core …

Readily available RGB-D cameras in smart phones and improving 3D scanning
technologies have made it possible to produce detailed point cloud and point-based models …

The 3D laser scanning has increasingly been applied in the field of monitoring roadway
deformation. Different from a terrestrial laser scanner (TLS), a mobile laser scanner (MLS) is …

Point cloud is a critical 3D representation with many emerging applications. Because of the
point sparsity and irregularity high-quality rendering of point clouds is challenging and often …