Results 41 to 50 of about 6,559,013 (333)
Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion
Remote Sensing, 2022 The point cloud data from actual measurements are often sparse and incomplete, making it difficult to apply them directly to visual processing and 3D reconstruction.
Ruidong Hao +6 more
doaj +1 more source
Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting [PDF]
Computer Vision and Pattern Recognition, 2023 Predicting how the world can evolve in the future is crucial for motion planning in autonomous systems. Classical methods are limited because they rely on costly human annotations in the form of semantic class labels, bounding boxes, and tracks or HD ...
Tarasha Khurana +3 more
semanticscholar +1 more source
Linear-Based Incremental Co-Registration of MLS and Photogrammetric Point Clouds
Remote Sensing, 2021 Today, mobile laser scanning and oblique photogrammetry are two standard urban remote sensing acquisition methods, and the cross-source point-cloud data obtained using these methods have significant differences and complementarity.
Shiming Li +4 more
doaj +1 more source
Consistent ICP for the registration of sparse and inhomogeneous point clouds [PDF]
, 2016 In this paper, we derive a novel iterative closest point (ICP) technique that performs point cloud alignment in a robust and consistent way. Traditional ICP techniques minimize the point-to-point distances, which are successful when point clouds contain ...
Goeman, Werner +3 more
core +1 more source
Unsupervised Deep Probabilistic Approach for Partial Point Cloud Registration [PDF]
Computer Vision and Pattern Recognition, 2023 Deep point cloud registration methods face challenges to partial overlaps and rely on labeled data. To address these issues, we propose UDPReg, an unsupervised deep probabilistic registration framework for point clouds with partial overlaps. Specifically,
Guofeng Mei +7 more
semanticscholar +1 more source
Point Cloud Pre-Training with Diffusion Models [PDF]
Computer Vision and Pattern Recognition, 2023 Pre-training a model and then fine-tuning it on down-stream tasks has demonstrated significant success in the 2D image and NLP domains. However, due to the unordered and non-uniform density characteristics of point clouds, it is non-trivial to explore ...
Xiao Zheng +7 more
semanticscholar +1 more source
NICP: Dense normal based point cloud registration [PDF]
, 2015 In this paper we present a novel on-line method to recursively align point clouds. By considering each point together with the local features of the surface (normal and curvature), our method takes advantage of the 3D structure around the points for the ...
Grisetti, Giorgio, Serafin, Jacopo
core +1 more source
Self-Positioning Point-Based Transformer for Point Cloud Understanding [PDF]
Computer Vision and Pattern Recognition, 2023 Transformers have shown superior performance on various computer vision tasks with their capabilities to capture long-range dependencies. Despite the success, it is challenging to directly apply Transformers on point clouds due to their quadratic cost in
Jinyoung Park +4 more
semanticscholar +1 more source
Restoration of Individual Tree Missing Point Cloud Based on Local Features of Point Cloud
Remote Sensing, 2022 LiDAR (Light Detection And Ranging) technology is an important means to obtain three-dimensional information of trees and vegetation. However, due to the influence of scanning mode, environmental occlusion and mutual occlusion between tree canopies and ...
Wei Cao, Jiayi Wu, Yufeng Shi, Dong Chen
doaj +1 more source
OneFormer3D: One Transformer for Unified Point Cloud Segmentation [PDF]
Computer Vision and Pattern Recognition, 2023 Semantic, instance, and panoptic segmentation of 3D point clouds have been addressed using task-specific models of distinct design. Thereby, the similarity of all seg-mentation tasks and the implicit relationship between them have not been utilized ...
Maksim Kolodiazhnyi +3 more
semanticscholar +1 more source