The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …

Three-dimensional models provide a volumetric representation of space which is important
for a variety of robotic applications including flying robots and robots that are equipped with …

In this paper we present a progressive compression method for point sampled models that is
specifically apt at dealing with densely sampled surface geometry. The compression is …

We present a versatile and complete free-form shape modeling framework for point-sampled
geometry. By combining unstructured point clouds with the implicit surface definition of the …

In recent years point-based geometry has gained increasing attention as an alternative
surface representation, both for efficient rendering and for flexible geometry processing of …

The state-of-the-art 2D-based dynamic point cloud (DPC) compression algorithm is the
video-based point cloud compression (V-PCC) developed by the Moving Pictures Experts …

In this article, a survey of the point cloud compression (PCC) methods by organizing them
with respect to the data structure, coding representation space, and prediction strategies is …

Widely adopted motion forecasting datasets sub-stitute the observed sensory inputs with
higher-level abstractions such as 3D boxes and polylines. These sparse shapes are inferred …

Point clouds are one of the most primitive and fundamental manifold representations.
Popular sources of point clouds are three-dimensional shape acquisition devices such as …

Airborne laser scanning technology (LiDAR) makes it easy to collect large amounts of point
data that sample the elevation of the terrain beneath. The LAS format has become the de …