Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more
and more popular in the 3D vision community due to their compactness and strong …

Volumetric video, which offers immersive viewing experiences, is gaining increasing
prominence. With its six degrees of freedom, it provides viewers with greater immersion and …

Point clouds upsampling is a challenging issue to generate dense and uniform point clouds
from the given sparse input. Most existing methods either take the end-to-end supervised …

Adversarial attack methods based on point manipulation for 3D point cloud classification
have revealed the fragility of 3D models yet the adversarial examples they produce are …

This paper introduces Neural Subdivision, a novel framework for data-driven coarse-to-fine
geometry modeling. During inference, our method takes a coarse triangle mesh as input and …

Abstract 3D Object Detectors (3D-OD) are crucial for understanding the environment in
many robotic tasks especially autonomous driving. Including 3D information via Lidar …

Point cloud upsampling is to densify a sparse point set acquired from 3D sensors, providing
a denser representation for the underlying surface. Existing methods divide the input points …

Point cloud completion aims to utilize algorithms to repair missing parts in 3D data for high-
quality point clouds. This technology is crucial for applications such as autonomous driving …

Despite the success of recent upsampling approaches generating high-resolution point sets
with uniform distribution and meticulous structures is still challenging. Unlike existing …

Completing an unordered partial point cloud is a challenging task. Existing approaches that
rely on decoding a latent feature to recover the complete shape, often lead to the completed …