Results 21 to 30 of about 6,391,115 (351)
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection [PDF]
Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality.
Yin Zhou, Oncel Tuzel
semanticscholar +1 more source
Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis [PDF]
Discrete point cloud objects lack sufficient shape descriptors of 3D geometries. In this paper, we present a novel method for aggregating hypothetical curves in point clouds.
Tiange Xiang+4 more
semanticscholar +1 more source
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency [PDF]
Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration. Despite the increasing popularity of introducing deep learning techniques in this field, spatial consistency, which is essentially ...
Xuyang Bai+7 more
semanticscholar +1 more source
Geodesics on Point Clouds [PDF]
We present a novel framework to compute geodesics on implicit surfaces and point clouds. Our framework consists of three parts, particle based approximate geodesics on implicit surfaces, Cartesian grid based approximate geodesics on point clouds, and geodesic correction.
Hongchuan Yu, Jian J. Zhang, Zheng Jiao
openaire +2 more sources
Self-Supervised Pretraining of 3D Features on any Point-Cloud [PDF]
Pretraining on large labeled datasets is a prerequisite to achieve good performance in many computer vision tasks like image recognition, video understanding etc.
Zaiwei Zhang+3 more
semanticscholar +1 more source
Picking Towels in Point Clouds [PDF]
Picking clothing has always been a great challenge in laundry or textile industry automation, especially when some clothes are of the same colors, material and entangled with each other. In order to solve the problem, we present a grasp pose determination method to pick towels placed in a laundry basket or on a table. In our method, it is not needed to
Wang, Xiaoman+5 more
openaire +3 more sources
Topological Point Cloud Clustering
Accepted at the 40th International Conference on Machine Learning (ICML), 2023.
Grande, Vincent P., Schaub, Michael T.
openaire +3 more sources
The Space, Place, Sound, and Memory: Immersive Experiences of the Past project was led by dr James Cook, in collaboration with the Digital Documentation and Innovation team at Historic Environment Scotland, Soluis Heritage, the Binchois Consort, and ...
Cook, James, Mirashrafi, Sophia
doaj +1 more source
PointMixup: Augmentation for Point Clouds [PDF]
This paper introduces data augmentation for point clouds by interpolation between examples. Data augmentation by interpolation has shown to be a simple and effective approach in the image domain. Such a mixup is however not directly transferable to point clouds, as we do not have a one-to-one correspondence between the points of two different objects ...
Chen, Y.+6 more
openaire +5 more sources
DPDist: Comparing Point Clouds Using Deep Point Cloud Distance [PDF]
We introduce a new deep learning method for point cloud comparison. Our approach, named Deep Point Cloud Distance (DPDist), measures the distance between the points in one cloud and the estimated surface from which the other point cloud is sampled. The surface is estimated locally and efficiently using the 3D modified Fisher vector representation.
Yizhak Ben-Shabat+2 more
openaire +4 more sources