Sparse point annotations for remote sensing image segmentation by Sixian Chan, Wangjie Zhou, Yanjing Lei, Chao Li, Jie Hu, Feng Hong

“…To address this issue, we propose the Point-Based Expand Network (PENet) for Remote Sensing Semantic Segmentation (RSSS). …”
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Multi-scale sparse convolution and point convolution adaptive fusion point cloud semantic segmentation method by Yuxuan Bi, Peng Liu, Tianyi Zhang, Jialin Shi, Caixia Wang

“…To address these issues, this paper proposes a novel approach based on adaptive fusion of multi-scale sparse convolution and point convolution. First, addressing the drawbacks of redundant feature extraction with existing sparse 3D convolutions, we introduce an asymmetric importance of space locations (IoSL) sparse 3D convolution module. …”
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Sparse point spread function-based multi-image optical encryption by Ning Xu, Dalong Qi, Long Cheng, Zhen Pan, Chengyu Zhou, Wenzhang Lin, Hongmei Ma, Yunhua Yao, Yuecheng Shen, Lianzhong Deng, Zhenrong Sun, Shian Zhang

“…This work introduces a lensless sparse point spread function-based multi-image optical encryption (sPSF-MOE) technique that addresses these challenges and enhances performance. …”
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Ground Segmentation Algorithm for Sloped Terrain and Sparse LiDAR Point Cloud by Victor Jimenez, Jorge Godoy, Antonio Artunedo, Jorge Villagra

“…On the other hand, using a graph-based approach with message passing achieves better results than simpler filtering or enhancement techniques, since data propagation compensates sparse distributions of LiDAR point clouds. Experiments are conducted with two different sources of information: nuScenes’s public dataset and an autonomous vehicle prototype. …”
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SPBA-Net point cloud object detection with sparse attention and box aligning by Haojie Sha, Qingrui Gao, Hao Zeng, Kai Li, Wang Li, Xuande Zhang, Xiaohui Wang

“…However, during voxelization and Bird’s Eye View transformation, local point cloud data often remains sparse due to non-target areas and noise points, posing a significant challenge for feature extraction. …”
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Multi-Neighborhood Sparse Feature Selection for Semantic Segmentation of LiDAR Point Clouds by Rui Zhang, Guanlong Huang, Fengpu Bao, Xin Guo

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Sloped Terrain Segmentation for Autonomous Drive Using Sparse 3D Point Cloud by Seoungjae Cho, Jonghyun Kim, Warda Ikram, Kyungeun Cho, Young-Sik Jeong, Kyhyun Um, Sungdae Sim

“…A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. …”
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Semantic Segmentation Method for High-Resolution Tomato Seedling Point Clouds Based on Sparse Convolution by Shizhao Li, Zhichao Yan, Boxiang Ma, Shaoru Guo, Hongxia Song

Subjects: “…3D point clouds…”
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Temporal Correlation Optimization for Accelerated 3D Sparse Convolution in Point Cloud Inference on CPU by Chen Zhu, Li Chen, Qunsong Ye, Wei Li, Zushuai Xie

Subjects: “…3D point cloud…”
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PTFNet: Robotic-Relevant, Single-View Obstacle Footprint Estimation From Sparse and Incomplete Point Clouds by Konrad P. Cop, Tomasz P. Trzcinski

“…Instead, it focuses on rendering a 2D representation directly from segmented sensor scans, even if the available points are very sparse. At its core, we propose a lightweight, multi-modal autoencoder that takes an input of a voxelized incomplete point cloud and outputs an estimated footprint that is directly applicable to the occupancy grid. …”
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RaGeoSense for smart home gesture recognition using sparse millimeter wave radar point clouds by Honghong Chen, Xiangyu Wang, Zhanjun Hao, Yuru Lu, Jingyu Li, Haozhe Zhang, Ben Xi

“…Abstract With the growing demand for contactless human–computer interaction in the smart home field, gesture recognition technology shows great market potential. In this paper, a sparse millimeter wave point cloud-based gesture recognition system, RaGeoSense, is proposed, which is designed for smart home scenarios. …”
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High-Precision Indoor Visible Light Positioning Using Deep Neural Network Based on the Bayesian Regularization With Sparse Training Point by Haiqi Zhang, Jiahe Cui, Lihui Feng, Aiying Yang, Huichao Lv, Bo Lin, Heqing Huang

“…In this letter, we propose an indoor visible light positioning technique that combines deep neural network based on the Bayesian Regularization (BR-DNN) with sparse diagonal training data set. Unlike other neural networks, which require a large number of training data points to locate accurately, we realize the high precision positioning with only 20 training points in a 1.8 m × 1.8 m × 2.1 m location area. …”
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Learnable Resized and Laplacian-Filtered U-Net: Better Road Marking Extraction and Classification on Sparse-Point-Cloud-Derived Imagery by Miguel Luis Rivera Lagahit, Xin Liu, Haoyi Xiu, Taehoon Kim, Kyoung-Sook Kim, Masashi Matsuoka

“…Our analysis demonstrates significant improvements, with F1-scores increasing from below 20% to above 75%, showing the effectiveness of our approach in improving road marking extraction and classification from sparse-point-cloud-derived imagery.…”
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Point cloud geometry compression based on the combination of interlayer residual and IRN concatenated residual by Meng Huang, Qian Xu, Wenxuan Xu

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Fast sparse representative tree splitting via local density for large-scale clustering by Renmin Wang, Jie Li

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A Tentative Detection of a Point Source in the Disk Gap of HD 100546 with VLT/SPHERE-IRDIS Sparse Aperture Masking Interferometry by Dori Blakely, Doug Johnstone, Tomas Stolker, Myriam Benisty, Jens Kammerer, Brodie J. Norfolk, William Thompson, Jean-Philippe Berger

“…We reanalyze VLT/SPHERE-IRDIS K- and H -band sparse aperture masking interferometry data of the transition disk HD 100546 observed in 2018 and 2021, respectively. …”
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Enhancing image quality in circular-view photoacoustic tomography using randomized detection points by Soheil Hakakzadeh, Praveenbalaji Rajendran, Zahra Kavehvash, Manojit Pramanik

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NRAP-RCNN: A Pseudo Point Cloud 3D Object Detection Method Based on Noise-Reduction Sparse Convolution and Attention Mechanism by Ziyue Zhou, Yongqing Jia, Tao Zhu, Yaping Wan

Subjects: “…pseudo point cloud…”
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A Systematic Survey of Sparse Clustering by Josephine Bernadette M. Benjamin, Miin-Shen Yang

“…In this paper, we review sparse clustering approaches that aim to cluster data sets while selecting and removing redundant and irrelevant features as well as noisy points and outliers. …”
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VirtualPainting: Addressing Sparsity with Virtual Points and Distance-Aware Data Augmentation for 3D Object Detection by Sudip Dhakal, Deyuan Qu, Dominic Carrillo, Mohammad Dehghani Tezerjani, Qing Yang

“…However, we found that these methods still grapple with the inherent sparsity of LiDAR point cloud data, primarily because fewer points are enriched with camera-derived features for sparsely distributed objects. …”
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