Current 3D object detection methods are heavily influenced by 2D detectors. In order to
leverage architectures in 2D detectors, they often convert 3D point clouds to regular grids …

Object class detection, also known as category-level object detection, has become one of
the most focused areas in computer vision in the new century. This article attempts to …

Abstract 3D object detection in point clouds is a challenging vision task that benefits various
applications for understanding the 3D visual world. Lots of recent research focuses on how …

The depth information of RGB-D sensors has greatly simplified some common challenges in
computer vision and enabled breakthroughs for several tasks. In this paper, we propose to …

Despite advances in feature representation, leveraging geometric relations is crucial for
establishing reliable visual correspondences under large variations of images. In this work …

We propose a new approach for semantic segmentation of 3D city models. Starting from an
SfM reconstruction of a street-side scene, we perform classification and facade splitting …

Invasive plants constitute one of the major causes of biodiversity loss, and its monitoring
plays an important role in the management of coastal ecological systems. This study aimed …

Current successful methods of 3D scene perception rely on the large-scale annotated point
cloud, which is tedious and expensive to acquire. In this paper, we propose Model2Scene, a …

This letter presents a novel rotation-invariant method for object detection from terrestrial 3-D
laser scanning point clouds acquired in complex urban environments. We utilize the Implicit …

Object detection in three-dimensional (3-D) laser scanning point clouds of complex urban
environment is a challenging problem. Existing methods are limited by their robustness to …