Supervised learning relies heavily on labeled datasets, but data annotation is time-
consuming and tedious work. To speed up annotation, in this paper, we propose a fast data …

We present a simple and effective tool for performing interactive 3D object annotation for 3D
object detection on LiDAR point clouds. Our annotation pipeline begins with a pre-labeling …

Automatic annotation of 3D objects in cluttered scenes shows its great importance to a
variety of applications. Nowadays, 3D point clouds, a new 3D representation of real-world …

The annotation of 3D point cloud datasets is an expensive and tedious task. To optimize the
annotation process, recent works have proposed the use of environments with higher levels …

In this work, we describe a new, general, and efficient method for unstructured point cloud
labeling. As the question of efficiently using deep Convolutional Neural Networks (CNNs) on …

In this work, we describe a new, general, and efficient method for unstructured point cloud
labeling. As the question of efficiently using deep Convolutional Neural Networks (CNNs) on …

For effective Computer Vision (CV) applications, one of the difficult challenges service robots
have to face concerns with complete scene understanding. Therefore, various strategies are …

While much exciting progress is being made in 3D reconstruction of scenes, object labeling
of 3D point cloud for indoor scenes has been left as a challenge issue. How should we …

Recent years have produced a variety of learning based methods in the context of computer
vision and robotics. Most of the recently proposed methods are based on deep learning …

In the study of Simultaneous Localization and Mapping (SLAM), the existence of dynamic
obstacles will have a great impact on it, and when there are many dynamic obstacles, it will …