4.7 Article

Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Review Optics

Review of computer-generated hologram algorithms for color dynamic holographic three-dimensional display

Dapu Pi et al.

Summary: Holographic three-dimensional display is an important technique that provides depth information without special eyewear. Computer-generated holograms have emerged as the most promising method for holographic display, but face challenges such as heavy computation burden and low image quality. Researchers have explored various algorithms to overcome these problems and achieve color dynamic holographic three-dimensional display.

LIGHT-SCIENCE & APPLICATIONS (2022)

Article Environmental Sciences

Reconstruction of Indoor Navigation Elements for Point Cloud of Buildings with Occlusions and Openings by Wall Segment Restoration from Indoor Context Labeling

Guangzu Liu et al.

Summary: This paper proposes a method to automatically reconstruct indoor navigation elements from unstructured 3D point cloud of buildings with occlusions and openings. The method uses the outline and occupancy information provided by the horizontal projection of the point cloud to guide wall segment restoration, simulates the scanning process of a laser scanner for segmentation, and identifies missing wall surfaces and hidden doors using projection statistical graphs and given rules. Experimental results show that the method can detect and reconstruct indoor navigation elements without viewpoint information, with low deviation in the reconstructed models and high completeness and correctness. However, the method has limitations in extracting thick doors with a large number of occluded, non-planar components.

REMOTE SENSING (2022)

Article Environmental Sciences

Apple LiDAR Sensor for 3D Surveying: Tests and Results in the Cultural Heritage Domain

Lorenzo Teppati Lose et al.

Summary: The launch of the new iPad Pro by Apple in March 2020 generated high interest and expectations, particularly due to the inclusion of the LiDAR sensor. This technology has implications for augmented and mixed reality applications, as well as surveying tasks. Several iOS apps have been developed to utilize the Apple LiDAR sensor for 3D data acquisition, but their performance and the positional accuracy of the acquired 3D point clouds have not been fully validated.

REMOTE SENSING (2022)

Article Materials Science, Multidisciplinary

Invalid point removal method based on error energy function in fringe projection profilometry

Kaifeng Zhu et al.

Summary: We propose a method based on an error energy function to remove invalid points in fringe patterns, which can efficiently remove invalid points in fringe patterns and improve the quality of 3D reconstruction data.

RESULTS IN PHYSICS (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Automated Point Cloud Completion for Occlusion Reduction in Aerial Lidar

Nina Singer et al.

Summary: Point cloud completion aims to infer missing regions of a point cloud by proposing a new method using self-organizing maps for hierarchical sampling, leading to improved accuracy in the results.

GEOSPATIAL INFORMATICS XII (2022)

Article Environmental Sciences

2D&3DHNet for 3D Object Classification in LiDAR Point Cloud

Wei Song et al.

Summary: This paper proposes a hybrid 2D and 3D Hough Net for accurate semantic analysis of LiDAR point clouds. The network combines global and local Hough features extracted from the point clouds using deep learning and nearest neighbor algorithms.

REMOTE SENSING (2022)

Article Environmental Sciences

PointNet plus plus Network Architecture with Individual Point Level and Global Features on Centroid for ALS Point Cloud Classification

Yang Chen et al.

Summary: This study proposed a modified PointNet++ network architecture that concentrates point-level and global features on the centroid point towards local features to facilitate classification. The approach also utilizes a modified Focal Loss function to address the extremely uneven category distribution on ALS point clouds.

REMOTE SENSING (2021)

Article Robotics

Point Set Voting for Partial Point Cloud Analysis

Junming Zhang et al.

Summary: This paper proposes a general model for partial point cloud analysis, inferring the latent feature encoding a complete point cloud by applying a point set voting strategy. The approach ensures robustness to partial observation and the ability to output multiple possible results.

IEEE ROBOTICS AND AUTOMATION LETTERS (2021)

Proceedings Paper Computer Science, Artificial Intelligence

PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths

Xin Wen et al.

Summary: This paper introduces a new perspective on point cloud completion task by formulating the prediction as a point cloud deformation process using a novel neural network named PMP-Net. PMP-Net predicts unique point moving paths for each point to improve the quality of the predicted complete shape through shortest total point moving distances. Experimental results on Completion3D and PCN datasets show advantages over state-of-the-art point cloud completion methods.

2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021 (2021)

Article Computer Science, Software Engineering

PCT: Point cloud transformer

Meng-Hao Guo et al.

Summary: This paper introduces a novel framework named Point Cloud Transformer (PCT) for point cloud learning, based on Transformer and enhanced by farthest point sampling and nearest neighbor search for better capturing local context. Extensive experiments demonstrate that the PCT achieves state-of-the-art performance on shape classification, part segmentation, semantic segmentation, and normal estimation tasks.

COMPUTATIONAL VISUAL MEDIA (2021)

Article Optics

PFNet: an unsupervised deep network for polarization image fusion

Junchao Zhang et al.

OPTICS LETTERS (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Point Cloud Completion by Skip-attention Network with Hierarchical Folding

Xin Wen et al.

2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2020)

Review Computer Science, Artificial Intelligence

Applications of 3D point cloud data in the construction industry: A fifteen-year review from 2004 to 2018

Qian Wang et al.

ADVANCED ENGINEERING INFORMATICS (2019)

Proceedings Paper Computer Science, Artificial Intelligence

TopNet: Structural Point Cloud Decoder

Lyne P. Tchapmi et al.

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)

Article Construction & Building Technology

SLAM-driven robotic mapping and registration of 3D point clouds

Pileun Kim et al.

AUTOMATION IN CONSTRUCTION (2018)

Proceedings Paper Computer Science, Artificial Intelligence

Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis

Angela Dai et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Article Computer Science, Artificial Intelligence

An overview of depth cameras and range scanners based on time-of-flight technologies

Radu Horaud et al.

MACHINE VISION AND APPLICATIONS (2016)

Article Computer Science, Software Engineering

Massive point cloud data management: Design, implementation and execution of a point cloud benchmark

Peter van Oosterom et al.

COMPUTERS & GRAPHICS-UK (2015)