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3D object detection, Point cloud, Deep learning
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3D object detection, autonomous driving, graph neural network,
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Saliency, Detection, Embedded entities, 3D point clouds,
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Annotations, Detectors, Object detection, Training data,
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Point cloud compression, Solid modeling, Laser radar, Costs,
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Feature extraction, Detectors, Object detection, Proposals,
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Object detection, Feature extraction, Laser radar,
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3D object detection, Vertical distribution characteristics,
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2205
3D object detection, Autonomous vehicles, Point cloud,
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Feature extraction, Convolution, Proposals, Kernel, Laser radar,
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2208
Encoding, Object detection, Solid modeling, Feature extraction,
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2208
LiDAR, Point clouds, 3D object detection, Deep learning
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2208
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2209
Proposals, Object detection, Point cloud compression, Detectors,
Training, Task analysis, Point cloud, 3D object detection, sample re-weighting
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2210
Feature extraction, Object detection, Proposals, Transfer learning,
Task analysis, Brain modeling, 3D object detection, autonomous driving
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2211
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2212
3D scene understanding, Self-supervised learning,
Weakly-supervised representation learning, Spectral clustering
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Dynamic Multitarget Detection Algorithm of Voxel Point Cloud Fusion
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2212
Feature extraction, Point cloud compression, Object detection,
Cameras, Heuristic algorithms, Autonomous vehicles, multi-feature fusion
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Domain-Adversarial-Guided Siamese Network for Unsupervised
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IEEE DOI
2212
Feature extraction, Mutual information, Protocols,
3-D object retrieval, cross-domain retrieval, multiview
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Yin, L.M.[Ling-Mei],
Tian, W.[Wei],
Wang, L.[Ling],
Wang, Z.[Zhiang],
Yu, Z.P.[Zhuo-Ping],
SPV-SSD: An Anchor-Free 3D Single-Stage Detector with
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Liu, K.C.[Kang-Cheng],
RM3D: Robust Data-Efficient 3D Scene Parsing via Traditional and Learnt
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IJCV(131), No. 1, January 2023, pp. 938-967.
Springer DOI
2303
BibRef
Ning, K.L.[Kang-Lin],
Liu, Y.F.[Yan-Fei],
Su, Y.Z.[Yan-Zhao],
Jiang, K.[Ke],
Point-Voxel and Bird-Eye-View Representation Aggregation Network for
Single Stage 3D Object Detection,
ITS(24), No. 3, March 2023, pp. 3223-3235.
IEEE DOI
2303
Feature extraction, Detectors, Point cloud compression,
Convolution, Transformers, Semantics, Point cloud,
vision transformer
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Pop, A.[Alexandru],
Domsa, V.[Victor],
Tamas, L.[Levente],
Rotation Invariant Graph Neural Network for 3D Point Clouds,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link
2303
Rotation Normalization. Then matching.
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Wang, Q.[Qiang],
Li, Z.Y.[Zi-Yu],
Zhu, D.J.[De-Jun],
Yang, W.K.[Wan-Kou],
LiDAR-only 3D object detection based on spatial context,
JVCIR(93), 2023, pp. 103805.
Elsevier DOI
2305
3D object detection, Convolutional neural network, LiDAR, Deep learning
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Shi, G.S.[Guang-Sheng],
Wang, K.[Ke],
Li, R.F.[Rui-Feng],
Ma, C.[Chao],
Real-Time Point Cloud Object Detection via Voxel-Point Geometry
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ITS(24), No. 6, June 2023, pp. 5971-5982.
IEEE DOI
2306
Proposals, Point cloud compression, Feature extraction,
Object detection, Representation learning, Geometry,
point clouds
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Wu, J.Q.[Jun-Qi],
Yao, W.[Wen],
Jia, S.[Shuai],
Jiang, T.S.[Ting-Song],
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Ma, C.[Chao],
Chen, X.Q.[Xiao-Qian],
Gradient-based sparse voxel attacks on point cloud object detection,
PR(160), 2025, pp. 111156.
Elsevier DOI
2501
Point cloud detection, Adversarial examples, Deep learning
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Tan, T.[Thon],
Lim, J.M.Y.[Joanne Mun-Yee],
Foo, J.J.[Ji Jinn],
Muniandy, R.[Ramachandran],
3D detection transformer: Set prediction of objects using point
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CVIU(236), 2023, pp. 103808.
Elsevier DOI
2310
Deep learning, 3D object detection, Point clouds, Transformers,
Single-stage detector
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Yang, Y.[Yiran],
Sun, X.[Xian],
Diao, W.H.[Wen-Hui],
Rong, X.[Xuee],
Yan, S.[Shiyao],
Yin, D.[Dongshuo],
Li, X.M.[Xin-Ming],
Optimal Partition Assignment for Universal Object Detection,
MultMed(25), 2023, pp. 7582-7593.
IEEE DOI
2311
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He, X.[Xuan],
Wang, Z.[Zian],
Lin, J.C.[Jia-Cheng],
Nai, K.[Ke],
Yuan, J.[Jin],
Li, Z.Y.[Zhi-Yong],
DO-SA&R: Distant Object Augmented Set Abstraction and Regression for
Point-Based 3D Object Detection,
IP(32), 2023, pp. 5852-5864.
IEEE DOI Code:
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2311
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Zhu, Y.J.[Yi-Jie],
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Liu, M.[Moyun],
Yao, L.[Lei],
Chen, Y.[Youping],
BF3D: Bi-directional fusion 3D detector with semantic sampling and
geometric mapping,
IVC(139), 2023, pp. 104835.
Elsevier DOI Code:
WWW Link.
2311
Deep learning, 3D object detection, Bi-directional fusion,
Semantic sampling, Geometric mapping
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Ning, Y.Q.[Ya-Qian],
Cao, J.[Jie],
Bao, C.[Chun],
Hao, Q.[Qun],
DVST: Deformable Voxel Set Transformer for 3D Object Detection from
Point Clouds,
RS(15), No. 23, 2023, pp. 5612.
DOI Link
2312
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Xie, L.[Liang],
Xu, G.D.[Guo-Dong],
Cai, D.[Deng],
He, X.F.[Xiao-Fei],
X-View: Non-Egocentric Multi-View 3D Object Detector,
IP(32), 2023, pp. 1488-1497.
IEEE DOI
2303
Feature extraction, Detectors, Laser radar,
Point cloud compression, Interpolation, Fuses, 3D object detection,
autonomous driving
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Liu, Z.[Zhe],
Huang, T.[Tengteng],
Li, B.[Bingling],
Chen, X.[Xiwu],
Wang, X.[Xi],
Bai, X.[Xiang],
EPNet++: Cascade Bi-Directional Fusion for Multi-Modal 3D Object
Detection,
PAMI(45), No. 7, July 2023, pp. 8324-8341.
IEEE DOI
2306
Point cloud compression, Feature extraction, Object detection,
Cameras, Laser radar, Detectors, 3D object detection,
consistency
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Xie, G.D.[Guang-Da],
Li, Y.[Yang],
Wang, Y.P.[Yan-Ping],
Li, Z.Y.[Zi-Yi],
Qu, H.Q.[Hong-Quan],
3D Point Cloud Object Detection Algorithm Based on Temporal
Information Fusion and Uncertainty Estimation,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
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Zheng, Z.J.[Zhi-Jie],
Huang, Z.C.[Zhi-Cong],
Zhao, J.W.[Jing-Wen],
Hu, H.F.[Hai-Feng],
Chen, D.[Dihu],
DTSSD: Dual-Channel Transformer-Based Network for Point-Based 3D
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SPLetters(30), 2023, pp. 798-802.
IEEE DOI
2307
Feature extraction, Transformers, Object detection,
Point cloud compression, Estimation, Encoding, transformer
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Li, C.Z.[Chun-Zheng],
Wang, G.[Gaihua],
Long, Q.[Qian],
Zhou, Z.S.[Zheng-Shu],
SGF3D: Similarity-guided fusion network for 3D object detection,
IVC(142), 2024, pp. 104895.
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LiDAR, 3D object detection, Multi-modal, Point cloud features
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Li, F.[Fan],
Zhang, X.[Xuchong],
Sun, H.B.[Hong-Bin],
Adversarial Obstacle Generation Against LiDAR-Based 3D Object
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MultMed(26), 2024, pp. 2686-2699.
IEEE DOI
2402
Laser radar, Point cloud compression, Sensors, Detectors,
Perturbation methods, Solid modeling, Adversarial attack,
point cloud perturbation
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An, P.[Pei],
Duan, Y.C.[Yu-Cong],
Huang, Y.L.[Yu-Liang],
Ma, J.[Jie],
Chen, Y.F.[Yan-Fei],
Wang, L.[Liheng],
Yang, Y.[You],
Liu, Q.[Qiong],
SP-Det: Leveraging Saliency Prediction for Voxel-Based 3D Object
Detection in Sparse Point Cloud,
MultMed(26), 2024, pp. 2795-2808.
IEEE DOI
2402
Task analysis, Point cloud compression, Feature extraction,
Laser radar, Detectors, Object detection, 3D object detection, voxel
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Lu, B.[Bin],
Sun, Y.[Yang],
Yang, Z.Y.[Zhen-Yu],
Song, R.[Ran],
Jiang, H.Y.[Hai-Yan],
Liu, Y.H.[Yong-Huai],
HRNet: 3D object detection network for point cloud with hierarchical
refinement,
PR(149), 2024, pp. 110254.
Elsevier DOI
2403
3D object detection, LiDAR point clouds, Multi-scale features,
Transformer, Dynamic sample selection, Hierarchical refinement
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Yu, C.B.[Chuan-Bo],
Peng, B.[Bo],
Huang, Q.M.[Qing-Ming],
Lei, J.J.[Jian-Jun],
PIPC-3Ddet: Harnessing Perspective Information and Proposal
Correlation for 3D Point Cloud Object Detection,
CirSysVideo(34), No. 3, March 2024, pp. 1508-1518.
IEEE DOI
2403
Feature extraction, Proposals, Point cloud compression,
Object detection, Correlation, Data mining, 3D object detection,
correlation reasoning
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Yu, T.[Ting],
Lin, X.J.[Xiao-Jun],
Wang, S.H.[Shu-Hui],
Sheng, W.G.[Wei-Guo],
Huang, Q.M.[Qing-Ming],
Yu, J.[Jun],
A Comprehensive Survey of 3D Dense Captioning:
Localizing and Describing Objects in 3D Scenes,
CirSysVideo(34), No. 3, March 2024, pp. 1322-1338.
IEEE DOI
2403
Survey, Captioning.
Survey, Object Localization. Task analysis, Visualization, Point cloud compression, Grounding,
Surveys, Solid modeling, 3D dense captioning,
3D point cloud
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Song, Z.Y.[Zi-Ying],
Jia, C.Y.[Cai-Yan],
Yang, L.[Lei],
Wei, H.Y.[Hai-Yue],
Liu, L.[Lin],
GraphAlign++: An Accurate Feature Alignment by Graph Matching for
Multi-Modal 3D Object Detection,
CirSysVideo(34), No. 4, April 2024, pp. 2619-2632.
IEEE DOI
2404
Point cloud compression, Feature extraction,
Object detection, Laser radar, Semantics, local graphs
BibRef
Song, Z.Y.[Zi-Ying],
Wei, H.Y.[Hai-Yue],
Bai, L.[Lin],
Yang, L.[Lei],
Jia, C.Y.[Cai-Yan],
GraphAlign: Enhancing Accurate Feature Alignment by Graph matching
for Multi-Modal 3D Object Detection,
ICCV23(3335-3346)
IEEE DOI
2401
BibRef
Zheng, Y.[Yu],
Duan, Y.[Yueqi],
Li, Z.[Zongtai],
Zhou, J.[Jie],
Lu, J.W.[Ji-Wen],
Learning Dynamic Scene-Conditioned 3D Object Detectors,
PAMI(46), No. 5, May 2024, pp. 2981-2996.
IEEE DOI
2404
Detectors, Task analysis, Point cloud compression, Object detection,
Feature extraction, scene-conditioned learning
BibRef
Li, J.A.[Jian-An],
Dong, S.C.[Shao-Cong],
Ding, L.[Lihe],
Xu, T.F.[Ting-Fa],
MsSVT++: Mixed-Scale Sparse Voxel Transformer With Center Voting for
3D Object Detection,
PAMI(46), No. 5, May 2024, pp. 3736-3752.
IEEE DOI
2404
Transformers, Detectors,
Point cloud compression, Windows, Object detection, voxel transformer
BibRef
Wang, Q.[Qide],
Liu, D.X.[Da-Xin],
Liu, Z.Y.[Zhen-Yu],
Xu, J.[Jiatong],
Tan, J.R.[Jiang-Rong],
3D Object Segmentation Using Cross-Window Point Transformer With
Latent Semantic Boundary Guidance,
MultMed(26), 2024, pp. 5951-5961.
IEEE DOI
2404
Point cloud compression, Transformers, Semantics, Task analysis, Robots,
Object segmentation, transformer
BibRef
Gao, A.[Aqi],
Pang, Y.W.[Yan-Wei],
Nie, J.[Jing],
Shao, Z.[Zhuang],
Cao, J.[Jiale],
Guo, Y.[Yishun],
Li, X.L.[Xue-Long],
ESGN: Efficient Stereo Geometry Network for Fast 3D Object Detection,
CirSysVideo(34), No. 4, April 2024, pp. 2000-2009.
IEEE DOI
2404
Feature extraction, Cameras,
Object detection, Detectors, Laser radar, Representation learning
BibRef
Xiao, K.[Kai],
Li, T.[Teng],
Li, J.[Jun],
Huang, D.[Da],
Peng, Y.Y.X.[Yuan-Yan-Xi],
Equal Emphasis on Data and Network: A Two-Stage 3D Point Cloud Object
Detection Algorithm with Feature Alignment,
RS(16), No. 2, 2024, pp. 249.
DOI Link
2402
BibRef
Feng, Y.F.[Yi-Fan],
Ji, S.Y.[Shu-Yi],
Liu, Y.S.[Yu-Shen],
Du, S.[Shaoyi],
Dai, Q.H.[Qiong-Hai],
Gao, Y.[Yue],
Hypergraph-Based Multi-Modal Representation for Open-Set 3D Object
Retrieval,
PAMI(46), No. 4, April 2024, pp. 2206-2223.
IEEE DOI
2403
Task analysis, Solid modeling, Point cloud compression,
Correlation, Data models, Feature extraction, Hypergraph, memory bank
BibRef
Li, Y.Y.[Yang-Yang],
Ou, Z.[Zejun],
Liu, G.Y.[Guang-Yuan],
Yang, Z.C.[Zi-Chen],
Chen, Y.Q.[Yan-Qiao],
Shang, R.H.[Rong-Hua],
Jiao, L.C.[Li-Cheng],
Three-Dimensional Point Cloud Object Detection Based on Feature
Fusion and Enhancement,
RS(16), No. 6, 2024, pp. 1045.
DOI Link
2403
BibRef
Li, J.J.[Jun-Jie],
Du, S.L.[Sheng-Li],
Liu, J.F.[Jian-Feng],
Chen, W.[Weibiao],
Tang, M.[Manfu],
Zheng, L.[Lei],
Wang, L.[Lianfa],
Ji, C.[Chunle],
Yu, X.[Xiao],
Yu, W.L.[Wan-Li],
Language guided 3D object detection in point clouds for MEP scenes,
IET-CV(18), No. 4, 2024, pp. 526-539.
DOI Link
2406
object detection
BibRef
Tang, Q.S.[Qing-Song],
Bai, X.Y.[Xin-Yu],
Guo, J.T.[Jin-Ting],
Pan, B.[Bolin],
Jiang, W.[Wuming],
DFAF3D:A dual-feature-aware anchor-free single-stage 3D detector for
point clouds,
IVC(129), 2023, pp. 104594.
Elsevier DOI
2301
Dual feature aware, Deformable offset self-attention,
Spatial-context feature extraction, 3D object detection
BibRef
Wang, C.H.[Chia-Hung],
Chen, H.W.[Hsueh-Wei],
Chen, Y.[Yi],
Hsiao, P.Y.[Pei-Yung],
Fu, L.C.[Li-Chen],
VoPiFNet: Voxel-Pixel Fusion Network for Multi-Class 3D Object
Detection,
ITS(25), No. 8, August 2024, pp. 8527-8537.
IEEE DOI
2408
Feature extraction, Laser radar, Cameras, Detectors,
Object detection, Point cloud compression, Multi-modal, deep learning
BibRef
Zhou, J.[Jing],
Lin, T.X.[Teng-Xing],
Gong, Z.X.[Zi-Xin],
Huang, X.H.[Xin-Han],
SIANet: 3D object detection with structural information augment
network,
IET-CV(18), No. 5, 2024, pp. 682-695.
DOI Link
2408
convolutional neural nets, feature extraction, object detection
BibRef
Gao, X.[Xiang],
Yang, R.H.[Rong-Hao],
Chen, X.W.[Xue-Wen],
Tan, J.X.[Jun-Xiang],
Liu, Y.[Yan],
Wang, Z.H.[Zhao-Hua],
Tan, J.H.[Jia-Hao],
Liu, H.[Huan],
A New Framework for Generating Indoor 3D Digital Models from Point
Clouds,
RS(16), No. 18, 2024, pp. 3462.
DOI Link
2410
BibRef
Wang, L.[Lin],
Sun, S.L.[Shi-Liang],
Zhao, J.[Jing],
VirPNet: A Multimodal Virtual Point Generation Network for 3D Object
Detection,
MultMed(26), 2024, pp. 10597-10609.
IEEE DOI
2411
Point cloud compression, Laser radar, Object detection,
Feature extraction, Cameras, Autonomous vehicles,
virtual point
BibRef
Zhang, Y.F.[Yi-Fan],
Hou, J.H.[Jun-Hui],
Yuan, Y.X.[Yi-Xuan],
A Comprehensive Study of the Robustness for LiDAR-Based 3D Object
Detectors Against Adversarial Attacks,
IJCV(132), No. 5, May 2024, pp. 1592-1624.
Springer DOI
2405
BibRef
Sun, Y.[Yang],
Lu, B.[Bin],
Liu, Y.H.[Yong-Huai],
Yang, Z.Y.[Zhen-Yu],
Behera, A.[Ardhendu],
Song, R.[Ran],
Yuan, H.[Hejin],
Jiang, H.Y.[Hai-Yan],
Exploiting Label Uncertainty for Enhanced 3D Object Detection From
Point Clouds,
ITS(25), No. 6, June 2024, pp. 6074-6089.
IEEE DOI
2406
Uncertainty, Point cloud compression, Object detection,
Feature extraction, Automobiles, Proposals, 3D object detection,
dynamic sample selection
BibRef
Xie, G.T.[Guo-Tao],
Chen, Z.Y.[Zhi-Yuan],
Gao, M.[Ming],
Hu, M.J.[Man-Jiang],
Qin, X.H.[Xiao-Hui],
PPF-Det: Point-Pixel Fusion for Multi-Modal 3D Object Detection,
ITS(25), No. 6, June 2024, pp. 5598-5611.
IEEE DOI
2406
Feature extraction, Point cloud compression, Object detection,
Laser radar, Detectors, Cameras, Autonomous driving,
intelligent transportation systems
BibRef
Xu, J.L.[Jiao-Long],
Wang, G.J.[Guo-Jun],
Zhang, X.[Xiao],
Wan, G.W.[Guo-Wei],
ACDet:
Attentive Cross-view Fusion for LiDAR-based 3D Object Detection,
3DV22(74-83)
IEEE DOI
2408
Solid modeling, Head, Laser radar, Fuses, Graphics processing units,
Object detection, 3D Object Detection, Point Cloud, Autonomous Driving
BibRef
Huang, J.D.[Jing-Dong],
Du, J.X.[Ji-Xiang],
Zhang, H.B.[Hong-Bo],
Liu, H.J.[Huai-Jin],
Semantics feature sampling for point-based 3D object detection,
IVC(149), 2024, pp. 105180.
Elsevier DOI
2408
3D object detection, Point clouds, RoI pooling, Sampling method
BibRef
Li, B.[Bing],
Chen, J.[Jie],
Li, X.[Xinde],
Xu, R.[Rui],
Li, Q.[Qian],
Cao, Y.[Yice],
Wu, J.[Jun],
Qu, L.[Lei],
Li, Y.[Yingsong],
Diniz, P.S.R.[Paulo S. R.],
VFL3D: A Single-Stage Fine-Grained Lightweight Point Cloud 3D Object
Detection Algorithm Based on Voxels,
ITS(25), No. 9, September 2024, pp. 12034-12048.
IEEE DOI
2409
Feature extraction, Point cloud compression,
Object detection, Convolution,
compact fine-grained self-attention augmented module
BibRef
Dao, M.Q.[Minh-Quan],
Berrio, J.S.[Julie Stephany],
Frémont, V.[Vincent],
Shan, M.[Mao],
Héry, E.[Elwan],
Worrall, S.[Stewart],
Practical Collaborative Perception: A Framework for Asynchronous and
Multi-Agent 3D Object Detection,
ITS(25), No. 9, September 2024, pp. 12163-12175.
IEEE DOI Code:
WWW Link.
2409
Collaboration, Vehicle-to-everything, Point cloud compression,
Bandwidth, Synchronization, Detectors, LiDAR
BibRef
Cong, R.X.[Rui-Xuan],
Sheng, H.[Hao],
Zhao, M.Y.[Ming-Yuan],
Yang, D.[Dazhi],
Wang, T.[Tun],
Chen, R.S.[Rong-Shan],
Shen, J.H.[Jia-Hao],
Multimodal Perception Integrating Point Cloud and Light Field for
Ship Autonomous Driving,
ITS(25), No. 9, September 2024, pp. 12477-12489.
IEEE DOI
2409
Marine vehicles, Light fields, Autonomous vehicles,
Point cloud compression, Laser radar,
3D object locating and tracking
BibRef
Li, Y.[Yingyan],
Fan, L.[Lue],
Liu, Y.[Yang],
Huang, Z.[Zehao],
Chen, Y.T.[Yun-Tao],
Wang, N.[Naiyan],
Zhang, Z.X.[Zhao-Xiang],
Fully Sparse Fusion for 3D Object Detection,
PAMI(46), No. 11, November 2024, pp. 7217-7231.
IEEE DOI
2410
Feature extraction, Laser radar, Cameras, Detectors,
Instance segmentation, Point cloud compression,
long-range perception
BibRef
Fan, B.[Baojie],
Zhang, K.[Kexin],
Tian, J.[Jiandong],
HCPVF: Hierarchical Cascaded Point-Voxel Fusion for 3D Object
Detection,
CirSysVideo(34), No. 10, October 2024, pp. 8997-9009.
IEEE DOI
2411
Feature extraction, Point cloud compression, Proposals, Object detection,
Detectors, Transformers, 3D object detection, BEV, point cloud
BibRef
Qiao, R.Z.[Ren-Zhong],
Ji, H.B.[Hong-Bing],
Zhu, Z.G.[Zhi-Gang],
Zhang, W.B.[Wen-Bo],
Local-to-Global Semantic Learning for Multi-View 3D Object Detection
From Point Cloud,
CirSysVideo(34), No. 10, October 2024, pp. 9371-9385.
IEEE DOI
2411
Semantics, Feature extraction, Point cloud compression,
Object detection, Laser radar, Detectors, long-range small objects
BibRef
Shu, J.[Jun],
Wu, Q.[Qi],
Tan, L.[Liang],
Shu, X.[Xinyi],
Wan, F.C.[Feng-Chun],
CWGA-Net: Center-Weighted Graph Attention Network for 3D object
detection from point clouds,
IVC(152), 2024, pp. 105314.
Elsevier DOI
2412
Autonomous driving, 3D object detection, Local graph encoding,
Center-weighted cross-attention, Cross-feature fusion module
BibRef
Wei, M.Q.[Ming-Qiang],
Chen, B.[Baian],
Nan, L.L.[Liang-Liang],
Xie, H.R.[Hao-Ran],
Gu, L.P.[Li-Ping],
Lu, D.[Dening],
Wang, F.L.[Fu Lee],
Li, Q.[Qing],
SimLOG: Simultaneous Local-Global Feature Learning for 3D Object
Detection in Indoor Point Clouds,
ITS(25), No. 12, December 2024, pp. 19482-19495.
IEEE DOI Code:
WWW Link.
2412
Feature extraction, Point cloud compression,
Representation learning, Object detection, Transformers,
global context aggregation
BibRef
Hou, H.R.[Hao-Ran],
Feng, M.T.[Ming-Tao],
Wu, Z.J.[Zi-Jie],
Dong, W.S.[Wei-Sheng],
Zhu, Q.[Qing],
Wang, Y.[Yaonan],
Mian, A.[Ajmal],
3D Object Detection From Point Cloud via Voting Step Diffusion,
CirSysVideo(34), No. 12, December 2024, pp. 12142-12157.
IEEE DOI Code:
WWW Link.
2501
Object detection, Point cloud compression, Diffusion models,
Proposals, Solid modeling, Task analysis, 3D object detection,
noise conditioned score network
BibRef
Li, J.[Junru],
Wang, Z.L.[Zhi-Ling],
Gong, D.[Diancheng],
Wang, C.C.[Chun-Chun],
SCNet3D: Rethinking the Feature Extraction Process of Pillar-Based 3D
Object Detection,
ITS(26), No. 1, January 2025, pp. 770-784.
IEEE DOI
2501
Feature extraction, Point cloud compression, Object detection,
Pedestrians, Data mining, Automobiles, Shape, SCNet3D
BibRef
Han, Y.H.[Yue-Hui],
Xu, C.[Can],
Xu, R.[Rui],
Qian, J.J.[Jian-Jun],
Xie, J.[Jin],
Masked Motion Prediction with Semantic Contrast for Point Cloud
Sequence Learning,
ECCV24(LXXVI: 414-431).
Springer DOI
2412
BibRef
Kang, M.[Minju],
Kong, T.[Taehun],
Kim, T.K.[Tae-Kyun],
Semi-Supervised 3D Object Detection with Channel Augmentation Using
Transformation Equivariance,
ICIP24(638-644)
IEEE DOI
2411
Training, Point cloud compression, Solid modeling, Navigation,
Training data, Object detection, Semi-supervised learning,
Data augmentation
BibRef
Kuroki, M.[Michihiro],
Yamasaki, T.[Toshihiko],
Explaining 3D Object Detection Through Shapley Value-Based
Attribution Map,
ICIP24(507-513)
IEEE DOI
2411
Point cloud compression, Laser radar, Explainable AI,
Object detection, Robustness, Explainable AI, Object Detection,
Shapley Value
BibRef
XU, C.F.[Chen-Feng],
Ling, H.[Huan],
Fidler, S.[Sanja],
Litany, O.[Or],
3DiffTection: 3D Object Detection with Geometry-Aware Diffusion
Features,
CVPR24(10617-10627)
IEEE DOI Code:
WWW Link.
2410
Adaptation models, Semantics, Object detection, Manuals,
Feature extraction, Diffusion models
BibRef
Wu, X.Y.[Xiao-Yang],
Jiang, L.[Li],
Wang, P.S.[Peng-Shuai],
Liu, Z.J.[Zhi-Jian],
Liu, X.H.[Xi-Hui],
Qiao, Y.[Yu],
Ouyang, W.L.[Wan-Li],
He, T.[Tong],
Zhao, H.S.[Heng-Shuang],
Point Transformer V3: Simpler, Faster, Stronger,
CVPR24(4840-4851)
IEEE DOI
2410
Point cloud compression, Training, Representation learning,
Technological innovation, Solid modeling, Accuracy, 3D Backbone,
3D Object Detection
BibRef
Hekimoglu, A.[Aral],
Schmidt, M.[Michael],
Marcos-Ramiro, A.[Alvaro],
Monocular 3D Object Detection with LiDAR Guided Semi Supervised
Active Learning,
WACV24(2335-2344)
IEEE DOI Code:
WWW Link.
2404
Training, Solid modeling, Laser radar, Uncertainty, Noise, Detectors,
Algorithms, Machine learning architectures, formulations,
Image recognition and understanding
BibRef
Lv, C.H.[Cong-Hao],
Jiang, P.[Ping],
Wang, M.[Meng],
Lin, L.X.[Li-Xin],
Chen, X.C.[Xue-Chen],
Deng, X.H.[Xiao-Heng],
Rdssd: 3D Single Stage Object Detector for Roadside Lidar Sensors,
ICIP24(3396-3402)
IEEE DOI
2411
Point cloud compression, Laser radar, Object detection, Detectors,
Sampling methods, 3D Object Detection, Roadside Sensors, Point Clouds
BibRef
Eskandar, G.[George],
An Empirical Study of the Generalization Ability of Lidar 3D Object
Detectors to Unseen Domains,
CVPR24(23815-23825)
IEEE DOI
2410
Training, Solid modeling, Laser radar, Detectors,
Sensor phenomena and characterization, Transformers
BibRef
Feng, T.[Tuo],
Wang, W.G.[Wen-Guan],
Ma, F.[Fan],
Yang, Y.[Yi],
LSK3DNet: Towards Effective and Efficient 3D Perception with Large
Sparse Kernels,
CVPR24(14916-14927)
IEEE DOI
2410
Training, Point cloud compression, Solid modeling,
Computational modeling, Neural networks, Aerodynamics,
3D object detection
BibRef
Wu, H.[Hai],
Zhao, S.[Shijia],
Huang, X.[Xun],
Wen, C.[Chenglu],
Li, X.[Xin],
Wang, C.[Cheng],
Commonsense Prototype for Outdoor Unsupervised 3D Object Detection,
CVPR24(14968-14977)
IEEE DOI Code:
WWW Link.
2410
Training, Accuracy, Laser radar, Prototypes, Detectors,
Object detection, 3D object detection, unsupervised learning, point clouds
BibRef
Gambashidze, A.[Alexander],
Dadukin, A.[Aleksandr],
Golyadkin, M.[Maxim],
Razzhivina, M.[Maria],
Makarov, I.[Ilya],
Weak-to-Strong 3D Object Detection with X-Ray Distillation,
CVPR24(15055-15064)
IEEE DOI Code:
WWW Link.
2410
Point cloud compression, Solid modeling, Limiting,
Computational modeling, Object detection, 3D detection, autonomous driving
BibRef
Chae, Y.[Yujeong],
Kim, H.[Hyeonseong],
Yoon, K.J.[Kuk-Jin],
Towards Robust 3D Object Detection with LiDAR and 4D Radar Fusion in
Various Weather Conditions,
CVPR24(15162-15172)
IEEE DOI
2410
Meteorological radar, Laser radar, Fuses, Spaceborne radar,
Object detection, Sensor phenomena and characterization
BibRef
Kannan, N.K.S.[Nitin Kumar Saravana],
Reuse, M.[Matthias],
Simon, M.[Martin],
Click, Crop & Detect: One-Click Offline Annotation for
Human-in-the-Loop 3D Object Detection on Point Clouds,
WAD24(4514-4525)
IEEE DOI
2410
Charge coupled devices, Point cloud compression, Training,
Annotations, Supervised learning, Crops, 3D object detection,
Offline detection
BibRef
Ma, T.[Tao],
Yang, X.M.[Xue-Meng],
Zhou, H.B.[Hong-Bin],
Li, X.[Xin],
Shi, B.[Botian],
Liu, J.J.[Jun-Jie],
Yang, Y.C.[Yu-Chen],
Liu, Z.Z.[Zhi-Zheng],
He, L.[Liang],
Qiao, Y.[Yu],
Li, Y.K.[Yi-Kang],
Li, H.S.[Hong-Sheng],
DetZero: Rethinking Offboard 3D Object Detection with Long-term
Sequential Point Clouds,
ICCV23(6713-6724)
IEEE DOI
2401
BibRef
Pei, Y.[Yu],
Zhao, X.[Xian],
Li, H.[Hao],
Ma, J.Y.[Jing-Yuan],
Zhang, J.W.[Jing-Wei],
Pu, S.L.[Shi-Liang],
Clusterformer: Cluster-based Transformer for 3D Object Detection in
Point Clouds,
ICCV23(6641-6650)
IEEE DOI
2401
BibRef
Liu, B.[Bojun],
Li, S.S.[Shan-Shan],
Sheng, X.[Xihua],
Li, L.[Li],
Liu, D.[Dong],
Joint Optimized Point Cloud Compression for 3d Object Detection,
ICIP23(1185-1189)
IEEE DOI
2312
BibRef
Deng, Y.Z.[Yuan-Zhi],
Chi, C.[Cheng],
Wen, H.[Huajie],
Zhou, Y.[Yang],
Xu, G.[Gang],
Shen, J.H.[Jian-Hao],
Context-Aware Fusion for 3D Object Detection in LiDAR-Camera Systems,
CVIDL23(601-608)
IEEE DOI
2403
Point cloud compression, Laser radar,
Detectors, Object detection, Benchmark testing, Sensor fusion, Point cloud
BibRef
Fan, L.[Lue],
Yang, Y.[Yuxue],
Mao, Y.M.[Yi-Ming],
Wang, F.[Feng],
Chen, Y.T.[Yun-Tao],
Wang, N.[Naiyan],
Zhang, Z.X.[Zhao-Xiang],
Once Detected, Never Lost: Surpassing Human Performance in Offline
LiDAR based 3D Object Detection,
ICCV23(19763-19772)
IEEE DOI Code:
WWW Link.
2401
BibRef
Wu, G.[Guile],
Cao, T.T.[Tong-Tong],
Liu, B.B.[Bing-Bing],
Chen, X.X.[Xing-Xin],
Ren, Y.[Yuan],
Towards Universal LiDAR-Based 3D Object Detection by Multi-Domain
Knowledge Transfer,
ICCV23(8635-8644)
IEEE DOI
2401
BibRef
Peri, N.[Neehar],
Li, M.T.[Meng-Tian],
Wilson, B.[Benjamin],
Wang, Y.X.[Yu-Xiong],
Hays, J.[James],
Ramanan, D.[Deva],
An Empirical Analysis of Range for 3D Object Detection,
BRAVO23(4076-4085)
IEEE DOI
2401
BibRef
Cheng, Z.Y.[Zhong-Yao],
Chen, C.[Cen],
Zhao, Z.Y.[Zi-Yuan],
Qian, P.S.[Pei-Sheng],
Li, X.L.[Xiao-Li],
Yang, X.[Xulei],
COCO-TEACH: A Contrastive Co-Teaching Network For Incremental 3D
Object Detection,
ICIP23(1990-1994)
IEEE DOI
2312
BibRef
Decatur, D.[Dale],
Lang, I.[Itai],
Hanocka, R.[Rana],
3D Highlighter: Localizing Regions on 3D Shapes via Text Descriptions,
CVPR23(20930-20939)
IEEE DOI
2309
BibRef
Wang, Y.J.[Ying-Jie],
Deng, J.J.[Jia-Jun],
Li, Y.[Yao],
Hu, J.[Jinshui],
Liu, C.[Cong],
Zhang, Y.[Yu],
Ji, J.M.[Jian-Min],
Ouyang, W.L.[Wan-Li],
Zhang, Y.[Yanyong],
Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object
Detection,
CVPR23(13394-13403)
IEEE DOI
2309
BibRef
Chen, A.[Anthony],
Zhang, K.[Kevin],
Zhang, R.R.[Ren-Rui],
Wang, Z.H.[Zi-Han],
Lu, Y.H.[Yu-Heng],
Guo, Y.D.[Yan-Dong],
Zhang, S.H.[Shang-Hang],
PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D
Object Detection,
CVPR23(5291-5301)
IEEE DOI
2309
BibRef
Lu, Y.H.[Yu-Heng],
Xu, C.F.[Chen-Feng],
Wei, X.B.[Xiao-Bao],
Xie, X.D.[Xiao-Dong],
Tomizuka, M.[Masayoshi],
Keutzer, K.[Kurt],
Zhang, S.H.[Shang-Hang],
Open-Vocabulary Point-Cloud Object Detection without 3D Annotation,
CVPR23(1190-1199)
IEEE DOI
2309
BibRef
Zhu, Z.Y.[Zi-Yue],
Meng, Q.[Qiang],
Wang, X.[Xiao],
Wang, K.[Ke],
Yan, L.J.[Liu-Jiang],
Yang, J.[Jian],
Curricular Object Manipulation in LiDAR-Based Object Detection,
CVPR23(1125-1135)
IEEE DOI
2309
BibRef
Lei, J.[Jiahui],
Deng, C.Y.[Cong-Yue],
Schmeckpeper, K.[Karl],
Guibas, L.J.[Leonidas J.],
Daniilidis, K.[Kostas],
EFEM: Equivariant Neural Field Expectation Maximization for 3D Object
Segmentation Without Scene Supervision,
CVPR23(4902-4912)
IEEE DOI
2309
BibRef
Malic, D.[Dušan],
Fruhwirth-Reisinger, C.[Christian],
Possegger, H.[Horst],
Bischof, H.[Horst],
SAILOR: Scaling Anchors via Insights into Latent Object
Representation,
WACV23(623-632)
IEEE DOI
2302
Training, Adaptation models, Solid modeling, Laser radar,
Object detection, Detectors, Algorithms: 3D computer vision
BibRef
Luo, Z.P.[Zhi-Peng],
Zhang, G.[Gongjie],
Zhou, C.Q.[Chang-Qing],
Liu, T.R.[Tian-Rui],
Lu, S.J.[Shi-Jian],
Pan, L.[Liang],
TransPillars: Coarse-to-Fine Aggregation for Multi-Frame 3D Object
Detection,
WACV23(4219-4228)
IEEE DOI
2302
Point cloud compression, Location awareness, Fuses,
Object detection, Benchmark testing, Algorithms: 3D computer vision
BibRef
Erabati, G.K.[Gopi Krishna],
Araujo, H.[Helder],
Li3DeTr: A LiDAR based 3D Detection Transformer,
WACV23(4239-4248)
IEEE DOI
2302
Point cloud compression, Knowledge engineering, Laser radar,
Convolution, Object detection
BibRef
Qian, X.L.[Xue-Lin],
Wang, L.[Li],
Zhu, Y.[Yi],
Zhang, L.[Li],
Fu, Y.W.[Yan-Wei],
Xue, X.Y.[Xiang-Yang],
ImpDet: Exploring Implicit Fields for 3D Object Detection,
WACV23(4249-4259)
IEEE DOI
2302
Location awareness, Representation learning,
Point cloud compression, Semantics, Object detection, segmentation
BibRef
Lee, D.[Daeun],
Kim, J.[Jinkyu],
Resolving Class Imbalance for LiDAR-based Object Detector by Dynamic
Weight Average and Contextual Ground Truth Sampling,
WACV23(682-691)
IEEE DOI
2302
Weight measurement, Training, Roads, Semantics, Detectors, Solids,
Algorithms: Image recognition and understanding (object detection, Robotics
BibRef
Yang, H.H.[Hong-Hui],
Liu, Z.L.[Zi-Li],
Wu, X.P.[Xiao-Pei],
Wang, W.X.[Wen-Xiao],
Qian, W.[Wei],
He, X.F.[Xiao-Fei],
Cai, D.[Deng],
Graph R-CNN: Towards Accurate 3D Object Detection with
Semantic-Decorated Local Graph,
ECCV22(VIII:662-679).
Springer DOI
2211
BibRef
Doll, S.[Simon],
Schulz, R.[Richard],
Schneider, L.[Lukas],
Benzin, V.[Viviane],
Enzweiler, M.[Markus],
Lensch, H.P.A.[Hendrik P. A.],
SpatialDETR: Robust Scalable Transformer-Based 3D Object Detection From
Multi-view Camera Images With Global Cross-Sensor Attention,
ECCV22(XXIX:230-245).
Springer DOI
2211
BibRef
Liu, C.[Chang],
Qian, X.Y.[Xiao-Yan],
Huang, B.X.[Bin-Xiao],
Qi, X.J.[Xiao-Juan],
Lam, E.[Edmund],
Tan, S.C.[Siew-Chong],
Wong, N.[Ngai],
Multimodal Transformer for Automatic 3D Annotation and Object Detection,
ECCV22(XXXVIII:657-673).
Springer DOI
2211
BibRef
Zhou, Z.X.[Zi-Xiang],
Zhao, X.C.[Xiang-Chen],
Wang, Y.[Yu],
Wang, P.[Panqu],
Foroosh, H.[Hassan],
CenterFormer: Center-Based Transformer for 3D Object Detection,
ECCV22(XXXVIII:496-513).
Springer DOI
2211
BibRef
Hwang, J.J.[Jyh-Jing],
Kretzschmar, H.[Henrik],
Manela, J.[Joshua],
Rafferty, S.[Sean],
Armstrong-Crews, N.[Nicholas],
Chen, T.[Tiffany],
Anguelov, D.[Dragomir],
CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for
Robust 3D Object Detection,
ECCV22(XXXVIII:388-405).
Springer DOI
2211
BibRef
Yin, J.[Junbo],
Zhou, D.F.[Ding-Fu],
Zhang, L.J.[Liang-Jun],
Fang, J.[Jin],
Xu, C.Z.[Cheng-Zhong],
Shen, J.B.[Jian-Bing],
Wang, W.G.[Wen-Guan],
ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object
Detection,
ECCV22(XXIX:17-33).
Springer DOI
2211
BibRef
Carranza-García, M.[Manuel],
Riquelme, J.C.[José C.],
Zakhor, A.[Avideh],
Temporal Axial Attention For Lidar-Based 3d Object Detection In
Autonomous Driving,
ICIP22(201-205)
IEEE DOI
2211
Laser radar, Pipelines, Object detection, Streaming media,
Feature extraction, autonomous driving, attention, deep learning,
object detection
BibRef
Chen, K.[Keng],
Zhou, F.[Feng],
Dai, J.[Ju],
Shen, P.[Pei],
Cai, X.Q.[Xing-Quan],
Zhang, F.Q.[Feng-Quan],
MCGNet: Multi-Level Context-aware and Geometric-aware Network for 3D
Object Detection,
ICIP22(1846-1850)
IEEE DOI
2211
Point cloud compression, Image edge detection, Object detection,
Performance gain, Feature extraction, Proposals, 3D Point Clouds,
3D Bounding Boxes
BibRef
Williams, F.[Francis],
Gojcic, Z.[Zan],
Khamis, S.[Sameh],
Zorin, D.[Denis],
Bruna, J.[Joan],
Fidler, S.[Sanja],
Litany, O.[Or],
Neural Fields as Learnable Kernels for 3D Reconstruction,
CVPR22(18479-18489)
IEEE DOI
2210
WWW Link. Training, Linear systems, Codes, Shape, Computational modeling,
Vision+graphics
BibRef
Zhang, C.[Cheng],
Wan, H.C.[Hao-Cheng],
Shen, X.Y.[Xin-Yi],
Wu, Z.Z.[Zi-Zhao],
PatchFormer: An Efficient Point Transformer with Patch Attention,
CVPR22(11789-11798)
IEEE DOI
2210
Point cloud compression, Shape, Computational modeling,
Transformers,
Vision+graphics
BibRef
Uy, M.A.[Mikaela Angelina],
Chang, Y.Y.[Yen-Yu],
Sung, M.[Minhyuk],
Goel, P.[Purvi],
Lambourne, J.[Joseph],
Birdal, T.[Tolga],
Guibas, L.J.[Leonidas J.],
Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to
Extrusion Cylinders,
CVPR22(11840-11850)
IEEE DOI
2210
Point cloud compression, Training, Solid modeling, Visualization,
Shape, Reverse engineering, Segmentation, Vision + graphics
BibRef
Zheng, W.[Wu],
Hong, M.X.[Ming-Xuan],
Jiang, L.[Li],
Fu, C.W.[Chi-Wing],
Boosting 3D Object Detection by Simulating Multimodality on Point
Clouds,
CVPR22(13628-13637)
IEEE DOI
2210
Measurement, Training, Laser radar, Semantics, Detectors, Filling,
Recognition: detection, categorization, retrieval,
Scene analysis and understanding
BibRef
Deng, S.H.[Sheng-Heng],
Liang, Z.H.[Zhi-Hao],
Sun, L.[Lin],
Jia, K.[Kui],
VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial
Attention,
CVPR22(8438-8447)
IEEE DOI
2210
Point cloud compression, Laser radar, Fuses, Benchmark testing,
Proposals, 3D from multi-view and sensors, retrieval
BibRef
Fan, L.[Lue],
Pang, Z.Q.[Zi-Qi],
Zhang, T.Y.[Tian-Yuan],
Wang, Y.X.[Yu-Xiong],
Zhao, H.[Hang],
Wang, F.[Feng],
Wang, N.[Naiyan],
Zhang, Z.X.[Zhao-Xiang],
Embracing Single Stride 3D Object Detector with Sparse Transformer,
CVPR22(8448-8458)
IEEE DOI
2210
Point cloud compression, Navigation, Detectors, Object detection,
Sensor phenomena and characterization, Transformers,
Navigation and autonomous driving
BibRef
Zhong, J.X.[Jia-Xing],
Zhou, K.[Kaichen],
Hu, Q.Y.[Qing-Yong],
Wang, B.[Bing],
Trigoni, N.[Niki],
Markham, A.[Andrew],
No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static
Models by Fitting Feature-level Space-time Surfaces,
CVPR22(8500-8510)
IEEE DOI
2210
Point cloud compression, Pain, Tracking, Computational modeling,
Dynamics, Surgery, 3D from multi-view and sensors,
Video analysis and understanding
BibRef
Xue, Y.J.[Yu-Jing],
Mao, J.G.[Jia-Geng],
Niu, M.Z.[Min-Zhe],
Xu, H.[Hang],
Mi, M.B.[Michael Bi],
Zhang, W.[Wei],
Wang, X.G.[Xiao-Gang],
Wang, X.C.[Xin-Chao],
Point2Seq: Detecting 3D Objects as Sequences,
CVPR22(8511-8520)
IEEE DOI
2210
Training, Solid modeling, Robot vision systems, Object detection,
Predictive models, Decoding, 3D from multi-view and sensors,
Robot vision
BibRef
Liu, C.D.[Chuan-Dong],
Gao, C.Q.[Chen-Qiang],
Liu, F.[Fangcen],
Liu, J.[Jiang],
Meng, D.Y.[De-Yu],
Gao, X.B.[Xin-Bo],
SS3D: Sparsely-Supervised 3D Object Detection from Point Cloud,
CVPR22(8418-8427)
IEEE DOI
2210
Training, Point cloud compression, Annotations, Filtering, Detectors,
Object detection, 3D from multi-view and sensors,
Robot vision
BibRef
Hu, J.S.K.[Jordan S.K.],
Kuai, T.S.[Tian-Shu],
Waslander, S.L.[Steven L.],
Point Density-Aware Voxels for LiDAR 3D Object Detection,
CVPR22(8459-8468)
IEEE DOI
2210
Point cloud compression, Laser radar, Navigation, Object detection,
Feature extraction,
Navigation and autonomous driving
BibRef
You, Y.R.[Yu-Rong],
Luo, K.[Katie],
Phoo, C.P.[Cheng Perng],
Chao, W.L.[Wei-Lun],
Sun, W.[Wen],
Hariharan, B.[Bharath],
Campbell, M.[Mark],
Weinberger, K.Q.[Kilian Q.],
Learning to Detect Mobile Objects from LiDAR Scans Without Labels,
CVPR22(1120-1130)
IEEE DOI
2210
Training, Laser radar, Navigation, Detectors,
Sensors, Recognition: detection, categorization, retrieval,
Transfer/low-shot/long-tail learning
BibRef
Schinagl, D.[David],
Krispel, G.[Georg],
Possegger, H.[Horst],
Roth, P.M.[Peter M.],
Bischof, H.[Horst],
OccAM's Laser: Occlusion-based Attribution Maps for 3D Object
Detectors on LiDAR Data,
CVPR22(1131-1140)
IEEE DOI
2210
Point cloud compression, Laser radar, Detectors,
Object detection, Recognition: detection,
Robot vision
BibRef
Scarpellini, G.[Gianluca],
Fiorini, S.[Stefano],
Giuliari, F.[Francesco],
Morerio, P.[Pietro],
del Bue, A.[Alessio],
DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D
Reassembly,
CVPR24(28098-28108)
IEEE DOI Code:
WWW Link.
2410
Training, Solid modeling, Noise reduction, Noise, Diffusion models,
Graph neural networks, diffusion model, puzzle
BibRef
Mohammadi, S.S.[Seyed Saber],
Wang, Y.M.[Yi-Ming],
Taiana, M.[Matteo],
Morerio, P.[Pietro],
del Bue, A.[Alessio],
SVP-Classifier: Single-View Point Cloud Data Classifier with Multi-view
Hallucination,
CIAP22(II:15-26).
Springer DOI
2205
BibRef
Chen, Q.X.[Qiu-Xiao],
Qi, X.J.[Xiao-Jun],
Song, Z.Q.[Zi-Qi],
Real-time Hierarchical Soft Attention-based 3D Object Detection in
Point Clouds,
ICPR22(2928-2934)
IEEE DOI
2212
Point cloud compression, Laser radar,
Robot vision systems, Object detection, Information filters, Real-time systems
BibRef
Sun, P.[Pei],
Tan, M.X.[Ming-Xing],
Wang, W.[Weiyue],
Liu, C.X.[Chen-Xi],
Xia, F.[Fei],
Leng, Z.Q.[Zhao-Qi],
Anguelov, D.[Dragomir],
SWFormer: Sparse Window Transformer for 3D Object Detection in Point
Clouds,
ECCV22(X:426-442).
Springer DOI
2211
BibRef
Duan, Y.[Yao],
Zhu, C.Y.[Chen-Yang],
Lan, Y.Q.[Yu-Qing],
Yi, R.J.[Ren-Jiao],
Liu, X.W.[Xin-Wang],
Xu, K.[Kai],
DisARM: Displacement Aware Relation Module for 3D Detection,
CVPR22(16959-16968)
IEEE DOI
2210
Training, Point cloud compression, Redundancy, Neural networks,
Object detection, Organizations, retrieval
BibRef
Zhang, Y.F.[Yi-Fan],
Hu, Q.Y.[Qing-Yong],
Xu, G.Q.[Guo-Quan],
Ma, Y.X.[Yan-Xin],
Wan, J.W.[Jian-Wei],
Guo, Y.L.[Yu-Lan],
Not All Points Are Equal: Learning Highly Efficient Point-based
Detectors for 3D LiDAR Point Clouds,
CVPR22(18931-18940)
IEEE DOI
2210
Point cloud compression, Laser radar, Robot vision systems,
Pipelines, Object detection, Detectors, Robot vision,
Scene analysis and understanding
BibRef
Wang, H.Y.[Hai-Yang],
Shi, S.S.[Shao-Shuai],
Yang, Z.[Ze],
Fang, R.Y.[Rong-Yao],
Qian, Q.[Qi],
Li, H.S.[Hong-Sheng],
Schiele, B.[Bernt],
Wang, L.W.[Li-Wei],
RBGNet: Ray-based Grouping for 3D Object Detection,
CVPR22(1100-1109)
IEEE DOI
2210
Point cloud compression, Solid modeling, Shape, Object detection,
Performance gain, Feature extraction, Recognition: detection,
grouping and shape analysis
BibRef
Wang, Y.K.[Yi-Kai],
Ye, T.Q.[Teng-Qi],
Cao, L.[Lele],
Huang, W.B.[Wen-Bing],
Sun, F.C.[Fu-Chun],
He, F.X.[Feng-Xiang],
Tao, D.C.[Da-Cheng],
Bridged Transformer for Vision and Point Cloud 3D Object Detection,
CVPR22(12104-12113)
IEEE DOI
2210
Point cloud compression, Scalability, Object detection,
Transformers,
Scene analysis and understanding
BibRef
Hahner, M.[Martin],
Sakaridis, C.[Christos],
Bijelic, M.[Mario],
Heide, F.[Felix],
Yu, F.[Fisher],
Dai, D.X.[Deng-Xin],
Van Gool, L.J.[Luc J.],
LiDAR Snowfall Simulation for Robust 3D Object Detection,
CVPR22(16343-16353)
IEEE DOI
2210
Point cloud compression, Training, Solid modeling, Laser radar,
Training data, Object detection, retrieval, Robot vision,
Recognition: detection
BibRef
Yu, H.X.[Hong-Xing],
Wu, J.J.[Jia-Jun],
Yi, L.[Li],
Rotationally Equivariant 3D Object Detection,
CVPR22(1446-1454)
IEEE DOI
2210
Representation learning, Point cloud compression, Deep learning,
Solid modeling, Computational modeling, Object detection,
Scene analysis and understanding
BibRef
Chen, Y.[Yukang],
Li, Y.W.[Yan-Wei],
Zhang, X.Y.[Xiang-Yu],
Sun, J.[Jian],
Jia, J.Y.[Jia-Ya],
Focal Sparse Convolutional Networks for 3D Object Detection,
CVPR22(5418-5427)
IEEE DOI
2210
Convolutional codes, Point cloud compression, Convolution,
Computational modeling, Object detection, Recognition: detection,
Deep learning architectures and techniques
BibRef
He, C.H.[Chen-Hang],
Li, R.H.[Rui-Huang],
Li, S.[Shuai],
Zhang, L.[Lei],
Voxel Set Transformer:
A Set-to-Set Approach to 3D Object Detection from Point Clouds,
CVPR22(8407-8417)
IEEE DOI
2210
Point cloud compression, Convolutional codes,
Stochastic processes, Distributed databases, Object detection, retrieval
BibRef
Misra, I.[Ishan],
Girdhar, R.[Rohit],
Joulin, A.[Armand],
An End-to-End Transformer Model for 3D Object Detection,
ICCV21(2886-2897)
IEEE DOI
2203
Point cloud compression, Solid modeling, Shape, Object detection,
Transformers,
Representation learning
BibRef
Liu, Z.[Ze],
Zhang, Z.[Zheng],
Cao, Y.[Yue],
Hu, H.[Han],
Tong, X.[Xin],
Group-Free 3D Object Detection via Transformers,
ICCV21(2929-2938)
IEEE DOI
2203
Point cloud compression, Training, Stacking, Object detection,
Detectors, Benchmark testing,
BibRef
Man, Y.Z.[Yun-Ze],
Weng, X.[Xinshuo],
Sivakumar, P.K.[Prasanna Kumar],
O'Toole, M.[Matthew],
Kitani, K.[Kris],
Multi-Echo LiDAR for 3D Object Detection,
ICCV21(3743-3752)
IEEE DOI
2203
Point cloud compression, Reflectivity, Laser radar,
Pulse measurements, Measurement by laser beam, Object detection,
Vision for robotics and autonomous vehicles
BibRef
Xu, Q.G.[Qian-Geng],
Zhou, Y.[Yin],
Wang, W.[Weiyue],
Qi, C.R.[Charles R.],
Anguelov, D.[Dragomir],
SPG: Unsupervised Domain Adaptation for 3D Object Detection via
Semantic Point Generation,
ICCV21(15426-15436)
IEEE DOI
2203
Point cloud compression, Semantics, Training data, Detectors,
Object detection, Reliability,
3D from multiview and other sensors
BibRef
Fan, L.[Lue],
Xiong, X.[Xuan],
Wang, F.[Feng],
Wang, N.Y.[Nai-Yan],
Zhang, Z.X.[Zhao-Xiang],
RangeDet: In Defense of Range View for LiDAR-based 3D Object
Detection,
ICCV21(2898-2907)
IEEE DOI
2203
Solid modeling, Image segmentation, Quantization (signal), Codes,
Semantics, Detection and localization in 2D and 3D, Stereo,
3D from multiview and other sensors
BibRef
Guan, T.R.[Tian-Rui],
Wang, J.[Jun],
Lan, S.Y.[Shi-Yi],
Chandra, R.[Rohan],
Wu, Z.X.[Zu-Xuan],
Davis, L.S.[Larry S.],
Manocha, D.[Dinesh],
M3DETR: Multi-representation, Multi-scale, Mutual-relation 3D Object
Detection with Transformers,
WACV22(2293-2303)
IEEE DOI
2202
Point cloud compression, Visualization,
Laser radar, Object detection,
3D Computer Vision Object Detection/Recognition/Categorization
BibRef
Qiu, S.[Shi],
Wu, Y.F.[Yun-Fan],
Anwar, S.[Saeed],
Li, C.Y.[Chong-Yi],
Investigating Attention Mechanism in 3D Point Cloud Object Detection,
3DV21(403-412)
IEEE DOI
WWW Link.
2201
Code, Object Detection. Point cloud compression, Service robots, Pipelines,
Object detection, Transformers, Reliability engineering
BibRef
Katageri, S.[Siddharth],
Kudari, S.V.[Shashidhar V],
Gunari, A.[Akshaykumar],
Tabib, R.A.[Ramesh Ashok],
Mudenagudi, U.[Uma],
ABD-Net: Attention Based Decomposition Network for 3D Point Cloud
Decomposition,
StruCo3D21(2049-2057)
IEEE DOI
2112
Geometry, Solid modeling, Shape, Deep architecture
BibRef
Katageri, S.[Siddharth],
Kulmi, S.[Sameer],
Tabib, R.A.[Ramesh Ashok],
Mudenagudi, U.[Uma],
PointDCCNet: 3D Object Categorization Network using Point Cloud
Decomposition,
WiCV21(2200-2208)
IEEE DOI
2109
Solid modeling, Shape,
Network topology, Superresolution, Benchmark testing, Topology
BibRef
Zhu, M.[Ming],
Ma, C.[Chao],
Ji, P.[Pan],
Yang, X.K.[Xiao-Kang],
Cross-Modality 3D Object Detection,
WACV21(3771-3780)
IEEE DOI
2106
Laser radar, Fuses,
Semantics, Object detection
BibRef
Chen, Y.[Ye],
Liu, J.X.[Jin-Xian],
Ni, B.B.[Bing-Bing],
Wang, H.[Hang],
Yang, J.C.[Jian-Cheng],
Liu, N.[Ning],
Li, T.[Teng],
Tian, Q.[Qi],
Shape Self-Correction for Unsupervised Point Cloud Understanding,
ICCV21(8362-8371)
IEEE DOI
2203
Point cloud compression, Deep learning, Analytical models, Shape,
Pipelines, Feature extraction,
Representation learning
BibRef
Yang, J.Y.[Ju-Young],
Ahn, P.[Pyunghwan],
Kim, D.Y.[Do-Yeon],
Lee, H.[Haeil],
Kim, J.[Junmo],
Progressive Seed Generation Auto-Encoder for Unsupervised Point Cloud
Learning,
ICCV21(6393-6402)
IEEE DOI
2203
Point cloud compression, Annotations, Focusing,
Feature extraction, Stereo,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Venkatesh, R.[Rahul],
Karmali, T.[Tejan],
Sharma, S.[Sarthak],
Ghosh, A.[Aurobrata],
Babu, R.V.[R. Venkatesh],
Jeni, L.A.[Lászlo A.],
Singh, M.[Maneesh],
Deep Implicit Surface Point Prediction Networks,
ICCV21(12633-12642)
IEEE DOI
2203
Point cloud compression, Solid modeling, Shape,
Computational modeling, Predictive models,
3D from multiview and other sensors
BibRef
Zou, L.[Longkun],
Tang, H.[Hui],
Chen, K.[Ke],
Jia, K.[Kui],
Geometry-Aware Self-Training for Unsupervised Domain Adaptation on
Object Point Clouds,
ICCV21(6383-6392)
IEEE DOI
2203
Point cloud compression, Geometry, Representation learning,
Location awareness, Shape, Semantics, Stereo,
BibRef
Mao, J.[Jiageng],
Niu, M.Z.[Min-Zhe],
Bai, H.Y.[Hao-Yue],
Liang, X.D.[Xiao-Dan],
Xu, H.[Hang],
Xu, C.J.[Chun-Jing],
Pyramid R-CNN: Towards Better Performance and Adaptability for 3D
Object Detection,
ICCV21(2703-2712)
IEEE DOI
2203
Point cloud compression, Solid modeling, Adaptation models,
Focusing, Object detection,
Vision for robotics and autonomous vehicles
BibRef
Cen, J.[Jun],
Yun, P.[Peng],
Cai, J.H.[Jun-Hao],
Wang, M.Y.[Michael Yu],
Liu, M.[Ming],
Open-set 3D Object Detection,
3DV21(869-878)
IEEE DOI
2201
Measurement, Point cloud compression, Upper bound, Laser radar,
Object detection, Open systems
BibRef
Brodeur, T.[Tristan],
Ali Akbarpour, H.[Hadi],
Suddarth, S.[Steve],
Point Cloud Object Segmentation Using Multi Elevation-Layer 2D
Bounding-Boxes,
WAAMI21(3910-3918)
IEEE DOI
2112
Measurement, Octrees, Merging, Object segmentation
BibRef
Hu, W.B.[Wen-Bo],
Zhao, H.S.[Heng-Shuang],
Jiang, L.[Li],
Jia, J.Y.[Jia-Ya],
Wong, T.T.[Tien-Tsin],
Bidirectional Projection Network for Cross Dimension Scene
Understanding,
CVPR21(14368-14377)
IEEE DOI
2111
Geometry, Visualization,
Semantics, Benchmark testing, Image representation
BibRef
Huang, C.[Chao],
Cao, Z.J.[Zhang-Jie],
Wang, Y.[Yunbo],
Wang, J.M.[Jian-Min],
Long, M.S.[Ming-Sheng],
MetaSets: Meta-Learning on Point Sets for Generalizable
Representations,
CVPR21(8859-8868)
IEEE DOI
2111
Geometry, Training, Deep learning, Solid modeling,
Benchmark testing
BibRef
Chen, H.W.[Hai-Wei],
Liu, S.C.[Shi-Chen],
Chen, W.K.[Wei-Kai],
Li, H.[Hao],
Hill, R.[Randall],
Equivariant Point Network for 3D Point Cloud Analysis,
CVPR21(14509-14518)
IEEE DOI
2111
Convolutional codes, Visualization,
Shape, Convolution, Computational modeling
BibRef
Zheng, W.[Wu],
Tang, W.L.[Wei-Liang],
Jiang, L.[Li],
Fu, C.W.[Chi-Wing],
SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud,
CVPR21(14489-14498)
IEEE DOI
2111
Training, Matched filters,
Shape, Detectors, Object detection
BibRef
Cheng, B.[Bowen],
Sheng, L.[Lu],
Shi, S.S.[Shao-Shuai],
Yang, M.[Ming],
Xu, D.[Dong],
Back-tracing Representative Points for Voting-based 3D Object
Detection in Point Clouds,
CVPR21(8959-8968)
IEEE DOI
2111
Location awareness, Visualization,
Object detection, Feature extraction, Proposals
BibRef
Li, Y.W.[Ying-Wei],
Qi, C.R.[Charles R.],
Zhou, Y.[Yin],
Liu, C.X.[Chen-Xi],
Anguelov, D.[Dragomir],
MoDAR: Using Motion Forecasting for 3D Object Detection in Point
Cloud Sequences,
CVPR23(9329-9339)
IEEE DOI
2309
BibRef
Qi, C.R.[Charles R.],
Zhou, Y.[Yin],
Najibi, M.[Mahyar],
Sun, P.[Pei],
Vo, K.[Khoa],
Deng, B.Y.[Bo-Yang],
Anguelov, D.[Dragomir],
Offboard 3D Object Detection from Point Cloud Sequences,
CVPR21(6130-6140)
IEEE DOI
2111
Training, Pipelines, Detectors,
Object detection, Semisupervised learning, Real-time systems
BibRef
Li, Z.C.[Zhi-Chao],
Wang, F.[Feng],
Wang, N.[Naiyan],
LiDAR R-CNN: An Efficient and Universal 3D Object Detector,
CVPR21(7542-7551)
IEEE DOI
2111
Laser radar, Costs,
Codes, Detectors, Real-time systems
BibRef
Fang, J.[Jin],
Zuo, X.X.[Xin-Xin],
Zhou, D.[Dingfu],
Jin, S.Z.[Sheng-Ze],
Wang, S.[Sen],
Zhang, L.J.[Liang-Jun],
LiDAR-Aug: A General Rendering-based Augmentation Framework for 3D
Object Detection,
CVPR21(4708-4718)
IEEE DOI
2111
Training, Laser radar, Neural networks,
Training data, Object detection, Detectors
BibRef
Xiao, C.X.[Chen-Xi],
Wachs, J.[Juan],
Triangle-Net: Towards Robustness in Point Cloud Learning,
WACV21(826-835)
IEEE DOI
2106
Service robots,
Surveillance, Neural networks, Feature extraction, Robustness
BibRef
Yang, Y.R.[Yi-Rong],
Fan, B.[Bin],
Liu, Y.C.[Yong-Cheng],
Lin, H.[Hua],
Zhang, J.Y.[Ji-Yong],
Liu, X.[Xin],
Cai, X.Y.[Xin-Yu],
Xiang, S.M.[Shi-Ming],
Pan, C.H.[Chun-Hong],
Deep Space Probing for Point Cloud Analysis,
ICPR21(10235-10242)
IEEE DOI
2105
Geometry, Convolution, Neural networks,
Benchmark testing, Convolutional neural networks
BibRef
Lin, H.[Hua],
Fan, B.[Bin],
Liu, Y.C.[Yong-Cheng],
Yang, Y.R.[Yi-Rong],
Pan, Z.[Zheng],
Shi, J.B.[Jian-Bo],
Pan, C.H.[Chun-Hong],
Xie, H.W.[Hui-Wen],
PointSpherical: Deep Shape Context for Point Cloud Learning in
Spherical Coordinates,
ICPR21(10266-10273)
IEEE DOI
2105
Solid modeling, Shape, Convolution, Semantics, Feature extraction
BibRef
Alliegro, A.[Antonio],
Boscaini, D.[Davide],
Tommasi, T.[Tatiana],
Joint Supervised and Self-Supervised Learning for 3D Real World
Challenges,
ICPR21(6718-6725)
IEEE DOI
2105
Solid modeling, Shape,
Transfer learning, Supervised learning, Intelligent agents
BibRef
Zhong, M.[Min],
Zeng, G.[Gang],
Enhanced Vote Network for 3D Object Detection in Point Clouds,
ICPR21(6624-6631)
IEEE DOI
2105
Aggregates, Face recognition,
Semantics, Object detection, Benchmark testing, Feature extraction
BibRef
Demilew, S.S.[Selameab S.],
Aghdam, H.H.[Hamed H.],
Laganičre, R.[Robert],
Petriu, E.M.[Emil M.],
FA3D: Fast and Accurate 3d Object Detection,
ISVC20(I:397-409).
Springer DOI
2103
BibRef
Krishna, O.[Onkar],
Irie, G.[Go],
Wu, X.M.[Xiao-Meng],
Kawanishi, T.[Takahito],
Kashino, K.[Kunio],
Adaptive Spotting: Deep Reinforcement Object Search in 3d Point Clouds,
ACCV20(III:257-272).
Springer DOI
2103
BibRef
Zhang, Y.[Yi],
Ye, Y.W.[Yu-Wen],
Xiang, Z.Y.[Zhi-Yu],
Gu, J.Q.[Jia-Qi],
Sdp-net: Scene Flow Based Real-time Object Detection and Prediction
from Sequential 3d Point Clouds,
ACCV20(I:140-157).
Springer DOI
2103
BibRef
Liu, X.,
Cao, J.,
Bi, Q.,
Wang, J.,
Shi, B.,
Wei, Y.,
Dense Point Diffusion for 3D Object Detection,
3DV20(762-770)
IEEE DOI
2102
Convolution, Object detection,
Feature extraction, Task analysis, Quantization (signal)
BibRef
Saltori, C.,
Lathuiličre, S.,
Sebe, N.,
Ricci, E.,
Galasso, F.,
SF-UDA3D: Source-Free Unsupervised Domain Adaptation for LiDAR-Based
3D Object Detection,
3DV20(771-780)
IEEE DOI
2102
Annotations, Detectors,
Adaptation models, Laser radar, Target tracking,
LiDAR data
BibRef
Han, W.[Wei],
Zhang, Z.D.[Zheng-Dong],
Caine, B.[Benjamin],
Yang, B.[Brandon],
Sprunk, C.[Christoph],
Alsharif, O.[Ouais],
Ngiam, J.Q.[Ji-Quan],
Vasudevan, V.[Vijay],
Shlens, J.[Jonathon],
Chen, Z.F.[Zhi-Feng],
Streaming Object Detection for 3-d Point Clouds,
ECCV20(XVIII:423-441).
Springer DOI
2012
BibRef
Huang, R.[Rui],
Zhang, W.Y.[Wan-Yue],
Kundu, A.[Abhijit],
Pantofaru, C.[Caroline],
Ross, D.A.[David A.],
Funkhouser, T.[Thomas],
Fathi, A.[Alireza],
An LSTM Approach to Temporal 3d Object Detection in Lidar Point Clouds,
ECCV20(XVIII:266-282).
Springer DOI
2012
BibRef
Du, H.Y.[Hong-Yuan],
Li, L.J.[Lin-Jun],
Liu, B.[Bo],
Vasconcelos, N.M.[Nuno M.],
Spot: Selective Point Cloud Voting for Better Proposal in Point Cloud
Object Detection,
ECCV20(XI:230-247).
Springer DOI
2011
BibRef
Zhu, X.G.[Xin-Ge],
Ma, Y.X.[Yue-Xin],
Wang, T.[Tai],
Xu, Y.[Yan],
Shi, J.P.[Jian-Ping],
Lin, D.[Dahua],
SSN: Shape Signature Networks for Multi-class Object Detection from
Point Clouds,
ECCV20(XXV:581-597).
Springer DOI
2011
BibRef
He, C.H.[Chen-Hang],
Li, R.H.[Rui-Huang],
Zhang, Y.B.[Ya-Bin],
Li, S.[Shuai],
Zhang, L.[Lei],
MSF: Motion-guided Sequential Fusion for Efficient 3D Object
Detection from Point Cloud Sequences,
CVPR23(5196-5205)
IEEE DOI
2309
BibRef
He, C.H.[Chen-Hang],
Zeng, H.[Hui],
Huang, J.Q.[Jian-Qiang],
Hua, X.S.[Xian-Sheng],
Zhang, L.[Lei],
Structure Aware Single-Stage 3D Object Detection From Point Cloud,
CVPR20(11870-11879)
IEEE DOI
2008
Feature extraction, Task analysis,
Detectors, Object detection, Periodic structures, Tensile stress
BibRef
Hu, P.,
Ziglar, J.,
Held, D.,
Ramanan, D.,
What You See is What You Get: Exploiting Visibility for 3D Object
Detection,
CVPR20(10998-11006)
IEEE DOI
2008
Laser radar,
Robot sensing systems, Cognition,
Object detection
BibRef
Qian, R.,
Garg, D.,
Wang, Y.,
You, Y.,
Belongie, S.,
Hariharan, B.,
Campbell, M.,
Weinberger, K.Q.,
Chao, W.,
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection,
CVPR20(5880-5889)
IEEE DOI
2008
Detectors, Object detection,
Laser radar, Pipelines, Quantization (signal), Estimation
BibRef
Qi, C.R.,
Chen, X.,
Litany, O.,
Guibas, L.J.,
ImVoteNet: Boosting 3D Object Detection in Point Clouds With Image
Votes,
CVPR20(4403-4412)
IEEE DOI
2008
Object detection, Proposals, Feature extraction, Poles and towers, Semantics
BibRef
Ahmed, S.M.,
Chew, C.M.,
Density-Based Clustering for 3D Object Detection in Point Clouds,
CVPR20(10605-10614)
IEEE DOI
2008
Task analysis, Object detection, Proposals, Semantics, Image segmentation
BibRef
Chen, Y.,
Liu, S.,
Shen, X.,
Jia, J.,
DSGN: Deep Stereo Geometry Network for 3D Object Detection,
CVPR20(12533-12542)
IEEE DOI
2008
Feature extraction,
Geometry, Object detection, Detectors, Laser radar
BibRef
Chen, J.T.[Jin-Tai],
Lei, B.W.[Bi-Wen],
Song, Q.Y.[Qing-Yu],
Ying, H.C.[Hao-Chao],
Chen, D.Z.[Danny Z.],
Wu, J.[Jian],
A Hierarchical Graph Network for 3D Object Detection on Point Clouds,
CVPR20(389-398)
IEEE DOI
2008
Shape, Semantics, Proposals,
Object detection, Convolution, Feature extraction
BibRef
Zhang, Y.,
Xiang, Z.,
Qiao, C.,
Chen, S.,
Accurate and Real-Time Object Detection Based on Bird's Eye View on
3D Point Clouds,
3DV19(214-221)
IEEE DOI
1911
Feature extraction, Object detection, Laser radar, Real-time systems,
object detection
BibRef
Lang, A.H.[Alex H.],
Vora, S.[Sourabh],
Caesar, H.[Holger],
Zhou, L.B.[Lu-Bing],
Yang, J.[Jiong],
Beijbom, O.[Oscar],
PointPillars: Fast Encoders for Object Detection From Point Clouds,
CVPR19(12689-12697).
IEEE DOI
2002
BibRef
Yang, Z.T.[Ze-Tong],
Jiang, L.[Li],
Sun, Y.N.[Ya-Nan],
Schiele, B.[Bernt],
Jia, J.Y.[Jia-Ya],
A Unified Query-based Paradigm for Point Cloud Understanding,
CVPR22(8531-8541)
IEEE DOI
2210
Point cloud compression, Shape, Pipelines, Semantics,
Feature extraction, grouping and shape analysis
BibRef
Yang, Z.T.[Ze-Tong],
Sun, Y.N.[Ya-Nan],
Liu, S.[Shu],
Shen, X.Y.[Xiao-Yong],
Jia, J.Y.[Jia-Ya],
STD: Sparse-to-Dense 3D Object Detector for Point Cloud,
ICCV19(1951-1960)
IEEE DOI
2004
computer graphics, feature extraction, image representation,
neural nets, object detection, STD, point cloud, Training
BibRef
Zhang, L.J.[Lun-Jun],
Yang, A.J.[Anqi Joyce],
Xiong, Y.W.[Yu-Wen],
Casas, S.[Sergio],
Yang, B.[Bin],
Ren, M.Y.[Meng-Ye],
Urtasun, R.[Raquel],
Towards Unsupervised Object Detection from LiDAR Point Clouds,
CVPR23(9317-9328)
IEEE DOI
2309
BibRef
Yang, B.[Bin],
Luo, W.J.[Wen-Jie],
Urtasun, R.[Raquel],
PIXOR: Real-time 3D Object Detection from Point Clouds,
CVPR18(7652-7660)
IEEE DOI
1812
Object detection, Detectors,
Feature extraction, Real-time systems, Computer architecture
BibRef
Zhou, Y.,
Tuzel, O.,
VoxelNet:
End-to-End Learning for Point Cloud Based 3D Object Detection,
CVPR18(4490-4499)
IEEE DOI
1812
Laser radar, Feature extraction, Shape, Proposals, Encoding
BibRef
Li, J.X.[Jia-Xin],
Lee, G.H.[Gim Hee],
USIP: Unsupervised Stable Interest Point Detection From 3D Point
Clouds,
ICCV19(361-370)
IEEE DOI
2004
Code, Interest Pointe.
WWW Link. feature extraction, learning (artificial intelligence),
object detection, probability,
Solid modeling
BibRef
Lev, J.,
Lim, J.H.,
Ouarti, N.,
Principal curvature of point cloud for 3D shape recognition,
ICIP17(610-614)
IEEE DOI
1803
Histograms, Noise measurement, Object recognition, Robustness,
Sensors, Shape, Histograms,
Principal curvature
BibRef
Takabe, A.,
Takehara, H.,
Kawai, N.,
Sato, T.,
Machida, T.,
Nakanishi, S.,
Yokoya, N.,
Moving object detection from a point cloud using photometric and
depth consistencies,
ICPR16(561-566)
IEEE DOI
1705
Cameras, Data models, Histograms, Measurement by laser beam,
Object detection, Solid modeling, Three-dimensional, displays
BibRef
Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Point Cloud Segmentation, Depth Object Segmentation .