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PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation [article]

Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia
2020 arXiv   pre-print
Instance segmentation is an important task for scene understanding. Compared to the fully-developed 2D, 3D instance segmentation for point clouds have much room to improve.  ...  In this paper, we present PointGroup, a new end-to-end bottom-up architecture, specifically focused on better grouping the points by exploring the void space between objects.  ...  . • We propose a bottom-up 3D instance segmentation framework, named PointGroup, to deal with the challenging 3D instance segmentation task. • We propose a point clustering method based on dual coordinate  ... 
arXiv:2004.01658v1 fatcat:atrq6kbukjf35mz3mipb7ffvcy

PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation

Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, Jiaya Jia
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Instance segmentation is an important task for scene understanding. Compared to the fully-developed 2D, 3D instance segmentation for point clouds have much room to improve.  ...  In this paper, we present PointGroup, a new endto-end bottom-up architecture, specifically focused on better grouping the points by exploring the void space between objects.  ...  . • We propose a bottom-up 3D instance segmentation framework, named PointGroup, to deal with the challenging 3D instance segmentation task. • We propose a point clustering method based on dual coordinate  ... 
doi:10.1109/cvpr42600.2020.00492 dblp:conf/cvpr/JiangZS0FJ20 fatcat:qexojukex5asdljhnni7m6bqum

HIDA: Towards Holistic Indoor Understanding for the Visually Impaired via Semantic Instance Segmentation with a Wearable Solid-State LiDAR Sensor [article]

Huayao Liu, Ruiping Liu, Kailun Yang, Jiaming Zhang, Kunyu Peng, Rainer Stiefelhagen
2021 arXiv   pre-print
After the 3D instance segmentation, we post-process the segmented point cloud by removing outliers and projecting all points onto a top-view 2D map representation.  ...  To tackle these issues, we propose HIDA, a lightweight assistive system based on 3D point cloud instance segmentation with a solid-state LiDAR sensor, for holistic indoor detection and avoidance.  ...  After that, the captured point cloud will be sent to the segmentation network for 3D instance segmentation. 3D Instance Segmentation In the data preprocessing stage, if the point cloud is too large,  ... 
arXiv:2107.03180v1 fatcat:ttzevemruvhavghufz4e2r6pky

PST: Plant Segmentation Transformer Enhanced Phenotyping of MLS Oilseed Rape Point Cloud [article]

Ruiming Du, Zhihong Ma, Pengyao Xie, Haiyan Cen, Yong He
2022 arXiv   pre-print
The results proved that PST and PST-PointGroup (PG) achieved state-of-the-art performance in semantic and instance segmentation tasks.  ...  PST is composed of: (i) a dynamic voxel feature encoder (DVFE) to aggregate per point features with raw spatial resolution; (ii) dual window sets attention block to capture the contextual information;  ...  Instance segmentation head in PointGroup This section briefly revisits the instance segmentation head in PG for completeness.  ... 
arXiv:2206.13082v1 fatcat:sxa5jtseofcvtks346wxhxvsae

Hierarchical Aggregation for 3D Instance Segmentation [article]

Shaoyu Chen, Jiemin Fang, Qian Zhang, Wenyu Liu, Xinggang Wang
2021 arXiv   pre-print
for preliminarily clustering points to sets and set aggregation for generating complete instances from sets.  ...  Instance segmentation on point clouds is a fundamental task in 3D scene perception.  ...  PointGroup [20] proposes to cluster points based on dual coordinate sets and designs ScoreNet to predict scores for instances.  ... 
arXiv:2108.02350v1 fatcat:d6hvyhtfyvc4jkhcvo7lzeyryi

STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset [article]

Meida Chen, Qingyong Hu, Thomas Hugues, Andrew Feng, Yu Hou, Kyle McCullough, Lucio Soibelman
2022 arXiv   pre-print
Although various 3D datasets with different functions and scales have been proposed recently, it remains challenging for individuals to complete the whole pipeline of large-scale data collection, sanitization  ...  Motivated by this, we explore the procedurally synthetic 3D data generation paradigm to equip individuals with the full capability of creating large-scale annotated photogrammetry point clouds.  ...  Note that different instances are displayed in different random colors. Best viewed in color. : Pointgroup: Dual-set point grouping for 3d instance segmentation.  ... 
arXiv:2203.09065v1 fatcat:jjosk5xwsfhx7jguehkbveqip4

Sparse Cross-Scale Attention Network for Efficient LiDAR Panoptic Segmentation

Shuangjie Xu, Rui Wan, Maosheng Ye, Xiaoyi Zou, Tongyi Cao
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially for large instances, and  ...  For the surface-aggregated points, SCAN adopts a novel sparse class-agnostic representation of instance centroids, which can not only maintain the sparsity of aligned features to solve the under-segmentation  ...  PointGroup (Jiang et al. 2020) proposes a dual-clustering method to refine inaccurate offset predictions around object boundaries.  ... 
doi:10.1609/aaai.v36i3.20197 fatcat:d3ip43iix5appbzrwx52kclgtu

Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentation [article]

Shuangjie Xu, Rui Wan, Maosheng Ye, Xiaoyi Zou, Tongyi Cao
2022 arXiv   pre-print
Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially for large instances, and  ...  For the surface-aggregated points, SCAN adopts a novel sparse class-agnostic representation of instance centroids, which can not only maintain the sparsity of aligned features to solve the under-segmentation  ...  PointGroup (Jiang et al. 2020) proposes a dual-clustering method to refine inaccurate offset predictions around object boundaries.  ... 
arXiv:2201.05972v1 fatcat:c5mlp7qv4fe3rns5zqpburfbbi

Point Scene Understanding via Disentangled Instance Mesh Reconstruction [article]

Jiaxiang Tang, Xiaokang Chen, Jingbo Wang, Gang Zeng
2022 arXiv   pre-print
Semantic scene reconstruction from point cloud is an essential and challenging task for 3D scene understanding.  ...  To circumvent the hurdle, we propose a Disentangled Instance Mesh Reconstruction (DIMR) framework for effective point scene understanding.  ...  For example, PointGroup [37] uses sparse 3D CNNs [23, 69, 45, 59] to extract point cloud features, and propose a dual-set clustering algorithm to better distinguish the void space between object instances  ... 
arXiv:2203.16832v2 fatcat:umhqlzcierh6pclnaf77avvqm4

Language-Grounded Indoor 3D Semantic Segmentation in the Wild [article]

David Rozenberszki, Or Litany, Angela Dai
2022 arXiv   pre-print
However, current 3D semantic segmentation benchmarks contain only a small number of categories -- less than 30 for ScanNet and SemanticKITTI, for instance, which are not enough to reflect the diversity  ...  Extensive experiments show that our approach consistently outperforms state-of-the-art 3D pre-training for 3D semantic segmentation on our proposed benchmark (+9% relative mIoU), including limited-data  ...  Acknowledgements This project is funded by the Bavarian State Ministry of Science and the Arts and coordinated by the Bavarian Research Institute for Digital Transformation (bidt).  ... 
arXiv:2204.07761v2 fatcat:axlrozwpnjejnaarmeqrxyvgla

Deep Learning for 3D Point Clouds: A Survey [article]

Yulan Guo, Hanyun Wang, Qingyong Hu, Hao Liu, Li Liu, Mohammed Bennamoun
2020 arXiv   pre-print
It covers three major tasks, including 3D shape classification, 3D object detection and tracking, and 3D point cloud segmentation.  ...  To stimulate future research, this paper presents a comprehensive review of recent progress in deep learning methods for point clouds.  ...  A dual-set clustering algorithm and the ScoreNet is further utilized to achieve better grouping results.  ... 
arXiv:1912.12033v2 fatcat:qiiyvvuulfccxaiihf2mu23k34

PnP-3D: A Plug-and-Play for 3D Point Clouds [article]

Shi Qiu, Saeed Anwar, Nick Barnes
2021 arXiv   pre-print
With the help of the deep learning paradigm, many point cloud networks have been invented for visual analysis.  ...  However, there is great potential for development of these networks since the given information of point cloud data has not been fully exploited.  ...  Jia, “Pointgroup: Learning spatial contextual features for large-scale point cloud Dual-set point grouping for 3d instance  ... 
arXiv:2108.07378v2 fatcat:atpotz75ujg3rbcgm3qhkd72ay

VoteHMR: Occlusion-Aware Voting Network for Robust 3D Human Mesh Recovery from Partial Point Clouds [article]

Guanze Liu, Yu Rong, Lu Sheng
2021 arXiv   pre-print
3D human mesh recovery from point clouds is essential for various tasks, including AR/VR and human behavior understanding.  ...  for statistical 3D human models, such as SMPL.  ...  PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation. In Rodgers, and James Davis. 2005.  ... 
arXiv:2110.08729v1 fatcat:3b25xw26qraalbtuuejmiqedwy

Fooling LiDAR Perception via Adversarial Trajectory Perturbation [article]

Yiming Li and Congcong Wen and Felix Juefei-Xu and Chen Feng
2021 arXiv   pre-print
flag for the community.  ...  When autonomous vehicles are sending LiDAR point clouds to deep networks for perception and planning, could the motion compensation consequently become a wide-open backdoor in those networks, due to both  ...  gratefully acknowledge the useful comments and suggestions from Yong Xiao, Wenxiao Wang, Chenzhuang Du, Wang Zhao, Ziyuan Huang, Hang Zhao and Siheng Chen, and also thank Yan Wang, Shaoshuai Shi and Peiyun Wu for  ... 
arXiv:2103.15326v2 fatcat:sl5oygbamjfvnknb4hqmqr4bca

Hyperbolic band theory

Joseph Maciejko, Steven Rayan
2021 Science Advances  
Tanaka and thank the anonymous reviewers for very useful remarks and suggestions.  ...  S.R. was supported by NSERC Discovery Grant #RGPIN-2017-04520, the Canada Foundation for Innovation John R.  ...  For the specific case of the Bolza curve, we are able to examine the point-group action directly.  ... 
doi:10.1126/sciadv.abe9170 pmid:34516893 pmcid:PMC8442860 fatcat:2i3reu4drjhyrjyusxoqxvk6oq
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