Point cloud learning has lately attracted increasing attention due to its wide applications in
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one
of the most significant data formats for 3D representation and are gaining increased …

Abstract 3D instance segmentation, with a variety of applications in robotics and augmented
reality, is in large demands these days. Unlike 2D images that are projective observations of …

This paper presents one of the first learning-based NeRF 3D instance segmentation
pipelines, dubbed as Instance Neural Radiance Field, or Instance-NeRF. Taking a NeRF …

Point cloud sampling is a less explored research topic for this data representation. The most
commonly used sampling methods are still classical random sampling and farthest point …

3D segmentation is a fundamental and challenging problem in computer vision with
applications in autonomous driving and robotics. It has received significant attention from the …

We propose a novel method for instance label segmentation of dense 3D voxel grids. We
target volumetric scene representations, which have been acquired with depth sensors or …

Ecological resources are an important material foundation for the survival, development, and
self-realization of human beings. In-depth and comprehensive research and understanding …

Event cameras can perceive pixel-level brightness changes to output asynchronous event
streams, and have notable advantages in high temporal resolution, high dynamic range and …

This paper studies the 3D instance segmentation problem, which has a variety of real-world
applications such as robotics and augmented reality. Since the surroundings of 3D objects …