C Cheng, Q Sha, B He, G Li - Ocean Engineering, 2021 - Elsevier
Autonomous underwater vehicle plays a more and more important role in the exploration of marine resources. Path planning and obstacle avoidance is the core technology to realize …
Location information for events, assets, and individuals, mostly focusing on two dimensions so far, has triggered a multitude of applications across different verticals, such as consumer …
Abstract 3D point cloud data obtained from laser scans, images, and videos are able to provide accurate and fast records of the 3D geometries of construction-related objects. Thus …
With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the …
T Zheng, C Chen, J Yuan, B Li… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
Abstract 3D point-cloud recognition with PointNet and its variants has received remarkable progress. A missing ingredient, however, is the ability to automatically evaluate point-wise …
We research and develop autonomous mobile service robots as Collaborative Robots, ie, CoBots. For the last three years, our four CoBots have autonomously navigated in our multi …
JH Lee, CS Kim - Proceedings of the IEEE/CVF conference …, 2019 - openaccess.thecvf.com
We propose a novel algorithm for monocular depth estimation using relative depth maps. First, using a convolutional neural network, we estimate relative depths between pairs of …
A Kaiser, JA Ybanez Zepeda… - Computer Graphics …, 2019 - Wiley Online Library
The amount of captured 3D data is continuously increasing, with the democratization of consumer depth cameras, the development of modern multi‐view stereo capture setups and …
Exploiting fine-grained semantic features on point cloud data is still challenging because of its irregular and sparse structure in a non-Euclidean space. In order to represent the local …