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。
Article
Computer Science, Artificial Intelligence
Qingyong Hu et al.
Summary: This paper introduces SensatUrban, an urban-scale UAV photogrammetry point cloud dataset consisting of nearly three billion points collected from three UK cities, covering 7.6 km(2). It also provides fine-grained semantic annotations for each point in the dataset, making it three times larger than the previous largest photogrammetric point cloud dataset.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2022)
Article
Geography, Physical
Ravi Peters et al.
Summary: This paper presents a workflow for automatically reconstructing 3D building models using 2D building polygons and a lidar point cloud. The workflow generates models at different levels to meet the data requirements of various applications. It is designed to be robust and adaptable to algorithm improvements and new input data. The quality of the reconstructed data is monitored throughout the process, and a 3D viewer has been developed for viewing and downloading the data. The workflow has been applied to all 10 million buildings in the Netherlands and will be updated with new input data.
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Jin Huang et al.
Summary: This paper presents a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. The approach addresses the challenge of missing vertical walls by inferring them directly from the data. The method outperforms state-of-the-art methods in terms of reconstruction accuracy and robustness, as demonstrated in experiments on various large-scale airborne LiDAR point clouds. Additionally, the authors have generated a new dataset with their method, which can stimulate research in urban reconstruction and the use of 3D city models in urban applications.
Article
Computer Science, Software Engineering
Xianzhi Li et al.
Summary: In this article, a network architecture is introduced to process 3D point clouds using a new purely rotation-invariant representation, enabling better generalization to inputs at arbitrary orientations. The method preserves rotation invariance by encoding local and global information.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Engineering, Electrical & Electronic
Luyang Li et al.
Summary: This paper introduces a fast data structuring method called PSNet for retaining more local feature information in a point cloud. PSNet achieves grouping and sampling simultaneously, and has the advantages of stability and permutation invariance.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Haoxi Ran et al.
Summary: In this paper, a novel representation method called RepSurf is proposed to explicitly depict the very local structure of point clouds. It achieves better performance and efficiency than previous state-of-the-art methods in classification, segmentation, and detection tasks.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022)
(2022)
Article
Computer Science, Artificial Intelligence
Yulan Guo et al.
Summary: Recently, deep learning on point clouds has been gaining more attention, but it is still in its early stages due to the unique challenges faced in processing point clouds with deep neural networks.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Ying Li et al.
Summary: This article reviews the progress of deep learning in processing LiDAR point cloud data, particularly in the field of autonomous driving, including tasks such as segmentation, detection, and classification. Despite several studies focusing on computer vision topics for autonomous vehicles, there is still a research gap in the application of DL in LiDAR point cloud data for autonomous vehicles.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Tiange Xiang et al.
Summary: This paper presents a novel method for aggregating hypothetical curves in point clouds to enhance shape descriptors. The method involves grouping sequences of connected points by guided walks in the point clouds, and subsequently aggregating them. Experimental results demonstrate the effectiveness of the proposed method on several point cloud analysis tasks.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Feiran Li et al.
Summary: This study provides a detailed investigation of the PCA-based canonical poses of point clouds, revealing insufficient handling of ambiguity in recent works. The development of a simple pose selector module significantly improves classification accuracy on challenging real-world datasets, surpassing state-of-the-art approaches.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Francis Engelmann et al.
2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
(2020)
Review
Environmental Sciences
Lei Luo et al.
REMOTE SENSING OF ENVIRONMENT
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Francis Engelmann et al.
COMPUTER VISION - ECCV 2018 WORKSHOPS, PT III
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Jiancheng Yang et al.
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019)
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Chao Chen et al.
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019)
(2019)
Proceedings Paper
Imaging Science & Photographic Technology
Chenxi Zhao et al.
2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
(2019)
Proceedings Paper
Geosciences, Multidisciplinary
Meixia Jia et al.
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
(2019)
Article
Computer Science, Software Engineering
Alexandre Boulch et al.
COMPUTERS & GRAPHICS-UK
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Felix Jaremo Lawin et al.
COMPUTER ANALYSIS OF IMAGES AND PATTERNS
(2017)
Article
Statistics & Probability
Herve Abdi et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS
(2010)
