11.2.4.3 Point Cloud Object Detection

Chapter Contents (Back)
Object Detection. Object Segmentation. Point Cloud Segmentation.
See also Semi-Supervised Object Detection, 3D Object Detection. Object detection and Segmentation are very similar. More particularily:
See also Depth Object Detection, 3D Object Detection.
See also Semantic Object Detection, 3D, Depth.
See also Point Cloud Segmentation, Depth Object Segmentation.

Velizhev, A., Shapovalov, R., Schindler, K.,
Implicit Shape Models for Object Detection In 3d Point Clouds,
AnnalsPRS(I-3), No. 2012, pp. 179-184.
DOI Link 1209
BibRef

Sugimura, D.[Daisuke], Yamazaki, T.[Tomoaki], Hamamoto, T.[Takayuki],
Three-Dimensional Point Cloud Object Detection Using Scene Appearance Consistency Among Multi-View Projection Directions,
CirSysVideo(30), No. 10, October 2020, pp. 3345-3357.
IEEE DOI 2010
Object detection, Principal component analysis, Feature extraction, multi-viewpoint image analysis BibRef

Cheng, S.L.[Si-Lin], Chen, X.[Xiwu], He, X.W.[Xin-Wei], Liu, Z.[Zhe], Bai, X.[Xiang],
PRA-Net: Point Relation-Aware Network for 3D Point Cloud Analysis,
IP(30), 2021, pp. 4436-4448.
IEEE DOI 2104
Feature extraction, Shape, Aggregates, Kernel, Benchmark testing, Solid modeling, Point cloud, inter-region relations BibRef

Huang, T.T.[Teng-Teng], Liu, Z.[Zhe], Chen, X.[Xiwu], Bai, X.[Xiang],
EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection,
ECCV20(XV:35-52).
Springer DOI 2011
BibRef

Feng, M.T.[Ming-Tao], Gilani, S.Z.[Syed Zulqarnain], Wang, Y.N.[Yao-Nan], Zhang, L.[Liang], Mian, A.[Ajmal],
Relation Graph Network for 3D Object Detection in Point Clouds,
IP(30), 2021, pp. 92-107.
IEEE DOI 2011
Proposals, Object detection, Feature extraction, Laser radar, deep learning BibRef

Hsu, P.H.[Pai-Hui], Zhuang, Z.Y.[Zong-Yi],
Incorporating Handcrafted Features into Deep Learning for Point Cloud Classification,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Guarda, A.F.R.[André F. R.], Rodrigues, N.M.M.[Nuno M. M.], Pereira, F.[Fernando],
Neighborhood Adaptive Loss Function for Deep Learning-Based Point Cloud Coding With Implicit and Explicit Quantization,
MultMedMag(28), No. 3, July 2021, pp. 107-116.
IEEE DOI 2109
Encoding, Deep learning, Distortion, Geometry, Machine learning, Image coding, Point cloud coding, explicit quantization BibRef

Guarda, A.F.R.[André F. R.], Rodrigues, N.M.M.[Nuno M. M.], Pereira, F.[Fernando],
Point Cloud Geometry and Color Coding in a Learning-Based Ecosystem for JPEG Coding Standards,
ICIP23(2585-2589)
IEEE DOI 2312
BibRef

Ruivo, M.[Manuel], Guarda, A.F.R.[André F. R.], Pereira, F.[Fernando],
Learning-Based Rate Control for Learning-Based Point Cloud Geometry Coding,
ICIP23(251-255)
IEEE DOI 2312
BibRef

Seleem, A.[Abdelrahman], Guarda, A.F.R.[André F. R.], Rodrigues, N.M.M.[Nuno M. M.], Pereira, F.[Fernando],
Deep Learning-Based Compressed Domain Point Cloud Classification,
ICIP23(2620-2624)
IEEE DOI 2312
BibRef

Tian, Y.F.[Yi-Fei], Chen, L.[Long], Song, W.[Wei], Sung, Y.S.[Yun-Sick], Woo, S.C.[Sang-Chul],
DGCB-Net: Dynamic Graph Convolutional Broad Network for 3D Object Recognition in Point Cloud,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Su, F.[Fei], Zhu, H.H.[Hai-Hong], Chen, T.Y.[Tao-Yi], Li, L.[Lin], Yang, F.[Fan], Peng, H.X.[Hui-Xiang], Tang, L.[Lei], Zuo, X.K.[Xin-Kai], Liang, Y.F.[Yi-Fan], Ying, S.[Shen],
An anchor-based graph method for detecting and classifying indoor objects from cluttered 3D point clouds,
PandRS(172), 2021, pp. 114-131.
Elsevier DOI 2101
Point cloud, Object classification, Functional part, Graph matching, Super-graph, Graph similarity BibRef

Wang, Q.[Qi], Chen, J.[Jian], Deng, J.Q.[Jian-Qiang], Zhang, X.F.[Xin-Fang],
3D-CenterNet: 3D Object Detection Network for Point Clouds with Center Estimation Priority,
PR(115), 2021, pp. 107884.
Elsevier DOI 2104
3D object detection, Point cloud, Deep learning BibRef

Zhu, J.F.[Jian-Feng], Sui, L.C.[Li-Chun], Zang, Y.[Yufu], Zheng, H.[He], Jiang, W.[Wei], Zhong, M.[Mianqing], Ma, F.[Fei],
Classification of Airborne Laser Scanning Point Cloud Using Point-Based Convolutional Neural Network,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Brown, K.[Kyle], Bourbakis, N.[Nikolaos],
Curve and Surface Fitting Techniques in Computer Vision,
IJIG(21), No. 4, October 2021 2021, pp. 2150041.
DOI Link 2110
BibRef

Qian, R.[Rui], Lai, X.[Xin], Li, X.R.[Xi-Rong],
BADet: Boundary-Aware 3D Object Detection from Point Clouds,
PR(125), 2022, pp. 108524.
Elsevier DOI 2203
3D object detection, autonomous driving, graph neural network, boundary aware, point clouds BibRef

Arav, R.[Reuma], Filin, S.[Sagi],
A visual saliency-driven extraction framework of smoothly embedded entities in 3D point clouds of open terrain,
PandRS(188), 2022, pp. 125-140.
Elsevier DOI 2205
Saliency, Detection, Embedded entities, 3D point clouds, Geosites, Variational methods BibRef

Meng, Q.H.[Qing-Hao], Wang, W.G.[Wen-Guan], Zhou, T.F.[Tian-Fei], Shen, J.B.[Jian-Bing], Jia, Y.D.[Yun-De], Van Gool, L.J.[Luc J.],
Towards a Weakly Supervised Framework for 3D Point Cloud Object Detection and Annotation,
PAMI(44), No. 8, August 2022, pp. 4454-4468.
IEEE DOI 2207
Annotations, Detectors, Object detection, Training data, Solid modeling, 3D object detection, 3D annotation, autonomous driving BibRef

Hahner, M.[Martin], Sakaridis, C.[Christos], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather,
ICCV21(15263-15272)
IEEE DOI 2203
Point cloud compression, Solid modeling, Laser radar, Costs, Object detection, Mathematical models, Detection and localization in 2D and 3D BibRef

Yin, J.[Junbo], Shen, J.B.[Jian-Bing], Gao, X.[Xin], Crandall, D.J.[David J.], Yang, R.G.[Rui-Gang],
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection From Point Clouds,
PAMI(45), No. 8, August 2023, pp. 9822-9835.
IEEE DOI 2307
Feature extraction, Detectors, Object detection, Transformers, Spatiotemporal phenomena, Laser radar, Point cloud, transformer attention BibRef

Meng, Q.H.[Qing-Hao], Wang, W.G.[Wen-Guan], Zhou, T.F.[Tian-Fei], Shen, J.B.[Jian-Bing], Van Gool, L.J.[Luc J.], Dai, D.X.[Deng-Xin],
Weakly Supervised 3d Object Detection from Lidar Point Cloud,
ECCV20(XIII:515-531).
Springer DOI 2011
BibRef

Wang, G.J.[Guo-Jun], Wu, J.[Jian], Tian, B.[Bin], Teng, S.[Siyu], Chen, L.[Long], Cao, D.[Dongpu],
CenterNet3D: An Anchor Free Object Detector for Point Cloud,
ITS(23), No. 8, August 2022, pp. 12953-12965.
IEEE DOI 2208
Feature extraction, Detectors, Object detection, Proposals, Laser radar, Heating systems, Point cloud, autonomous vehicles, anchor free BibRef

Lin, C.M.[Chun-Mian], Tian, D.X.[Da-Xin], Duan, X.T.[Xu-Ting], Zhou, J.S.[Jian-Shan], Zhao, D.[Dezong], Cao, D.[Dongpu],
CL3D: Camera-LiDAR 3D Object Detection With Point Feature Enhancement and Point-Guided Fusion,
ITS(23), No. 10, October 2022, pp. 18040-18050.
IEEE DOI 2210
Object detection, Feature extraction, Laser radar, Location awareness, Semantics, Head, 3D object detection, intelligent transportation systems BibRef

Jung, W.[Woonhyung], Hyeon, J.[Janghun], Doh, N.[Nakju],
Robust Cuboid Modeling from Noisy and Incomplete 3D Point Clouds Using Gaussian Mixture Model,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Xiao, W.P.[Wei-Ping], Li, X.M.[Xiao-Mao], Liu, C.[Chang], Gao, J.T.[Jian-Tao], Luo, J.[Jun], Peng, Y.[Yan], Zhou, Y.[Yang],
3D-VDNet: Exploiting the vertical distribution characteristics of point clouds for 3D object detection and augmentation,
IVC(127), 2022, pp. 104557.
Elsevier DOI 2211
3D object detection, Vertical distribution characteristics, Object augmentation, LiDAR point cloud BibRef

Liang, Z.M.[Zhen-Ming], Huang, Y.P.[Ying-Ping], Liu, Z.W.[Zhen-Wei],
Efficient graph attentional network for 3D object detection from Frustum-based LiDAR point clouds,
JVCIR(89), 2022, pp. 103667.
Elsevier DOI 2212
3D object detection, Multi-sensors fusion, Graph convolutional networks, Attention mechanism, Autonomous driving BibRef

Zhang, J.[Jing], Wang, J.J.[Jia-Jun], Xu, D.[Da], Li, Y.S.[Yun-Song],
HCNET: A Point Cloud Object Detection Network Based on Height and Channel Attention,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Li, Z.Y.[Zi-Yu], Yao, Y.C.[Yun-Cong], Quan, Z.B.[Zhi-Bin], Xie, J.[Jin], Yang, W.K.[Wan-Kou],
Spatial information enhancement network for 3D object detection from point cloud,
PR(128), 2022, pp. 108684.
Elsevier DOI 2205
3D object detection, Autonomous vehicles, Point cloud, LiDAR sensor, 3D shape completion BibRef

Wang, M.M.[Ming-Ming], Chen, Q.K.[Qing-Kui], Fu, Z.B.[Zhi-Bing],
LSNet: Learned Sampling Network for 3D Object Detection from Point Clouds,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Wang, B.X.[Bing-Xu], Lan, J.H.[Jin-Hui], Gao, J.[Jiangjiang],
LiDAR Filtering in 3D Object Detection Based on Improved RANSAC,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Elich, C.[Cathrin], Oswald, M.R.[Martin R.], Pollefeys, M.[Marc], Stueckler, J.[Joerg],
Weakly supervised learning of multi-object 3D scene decompositions using deep shape priors,
CVIU(220), 2022, pp. 103440.
Elsevier DOI 2206
Multi-object 3D scene representation learning BibRef

Tian, Y.L.[Yong-Lin], Huang, L.C.[Li-Chao], Yu, H.[Hui], Wu, X.B.[Xiang-Bin], Li, X.S.[Xue-Song], Wang, K.F.[Kun-Feng], Wang, Z.[Zilei], Wang, F.Y.[Fei-Yue],
Context-Aware Dynamic Feature Extraction for 3D Object Detection in Point Clouds,
ITS(23), No. 8, August 2022, pp. 10773-10785.
IEEE DOI 2208
Feature extraction, Convolution, Proposals, Kernel, Laser radar, Semantics, Point clouds, 3D detection, dynamic network, context features BibRef

Ouyang, Z.C.[Zhen-Chao], Dong, X.Y.[Xiao-Yun], Cui, J.[Jiahe], Niu, J.W.[Jian-Wei], Guizani, M.[Mohsen],
PV-EncoNet: Fast Object Detection Based on Colored Point Cloud,
ITS(23), No. 8, August 2022, pp. 12439-12450.
IEEE DOI 2208
Encoding, Object detection, Solid modeling, Feature extraction, Data models, Convolution, Multi-Sensor fusion, point cloud, camera, self-driving BibRef

Ma, R.Q.[Rui-Qi], Chen, C.[Chi], Yang, B.S.[Bi-Sheng], Li, D.R.[De-Ren], Wang, H.P.[Hai-Ping], Cong, Y.Z.[Yang-Zi], Hu, Z.T.[Zong-Tian],
CG-SSD: Corner guided single stage 3D object detection from LiDAR point cloud,
PandRS(191), 2022, pp. 33-48.
Elsevier DOI 2208
LiDAR, Point clouds, 3D object detection, Deep learning BibRef

Zhao, Y.H.[Yong-Heng], Fang, G.C.[Guang-Chi], Guo, Y.L.[Yu-Lan], Guibas, L.J.[Leonidas J.], Tombari, F.[Federico], Birdal, T.[Tolga],
3DPointCaps++: Learning 3D Representations with Capsule Networks,
IJCV(130), No. 9, September 2022, pp. 2321-2336.
Springer DOI 2208
BibRef

Cai, Q.[Qi], Pan, Y.W.[Ying-Wei], Yao, T.[Ting], Mei, T.[Tao],
3D Cascade RCNN: High Quality Object Detection in Point Clouds,
IP(31), 2022, pp. 5706-5719.
IEEE DOI 2209
Proposals, Object detection, Point cloud compression, Detectors, Training, Task analysis, Point cloud, 3D object detection, sample re-weighting BibRef

Du, L.[Liang], Ye, X.Q.[Xiao-Qing], Tan, X.[Xiao], Johns, E.[Edward], Chen, B.[Bo], Ding, E.[Errui], Xue, X.Y.[Xiang-Yang], Feng, J.F.[Jian-Feng],
AGO-Net: Association-Guided 3D Point Cloud Object Detection Network,
PAMI(44), No. 11, November 2022, pp. 8097-8109.
IEEE DOI 2210
Feature extraction, Object detection, Proposals, Transfer learning, Task analysis, Brain modeling, 3D object detection, autonomous driving BibRef

Zhang, Q.J.[Qi-Jian], Hou, J.H.[Jun-Hui], Qian, Y.[Yue], Chan, A.B.[Antoni B.], Zhang, J.Y.[Ju-Yong], He, Y.[Ying],
RegGeoNet: Learning Regular Representations for Large-Scale 3D Point Clouds,
IJCV(130), No. 12, December 2022, pp. 3100-3122.
Springer DOI 2211

WWW Link. BibRef

Tian, B.[Beiwen], Luo, L.[Liyi], Zhao, H.[Hao], Zhou, G.[Guyue],
VIBUS: Data-efficient 3D scene parsing with VIewpoint Bottleneck and Uncertainty-Spectrum modeling,
PandRS(194), 2022, pp. 302-318.
Elsevier DOI 2212
3D scene understanding, Self-supervised learning, Weakly-supervised representation learning, Spectral clustering BibRef

Luo, X.Z.[Xi-Zhao], Zhou, F.[Feng], Tao, C.B.[Chong-Ben], Yang, A.[Anjia], Zhang, P.[Peiyun], Chen, Y.H.[Yong-Hua],
Dynamic Multitarget Detection Algorithm of Voxel Point Cloud Fusion Based on PointRCNN,
ITS(23), No. 11, November 2022, pp. 20707-20720.
IEEE DOI 2212
Feature extraction, Point cloud compression, Object detection, Cameras, Heuristic algorithms, Autonomous vehicles, multi-feature fusion BibRef

Liu, A.A.[An-An], Guo, F.B.[Fu-Bin], Zhou, H.Y.[He-Yu], Yan, C.G.[Cheng-Gang], Gao, Z.[Zan], Li, X.Y.[Xuan-Ya], Li, W.H.[Wen-Hui],
Domain-Adversarial-Guided Siamese Network for Unsupervised Cross-Domain 3-D Object Retrieval,
Cyber(52), No. 12, December 2022, pp. 13862-13873.
IEEE DOI 2212
Feature extraction, Mutual information, Protocols, 3-D object retrieval, cross-domain retrieval, multiview BibRef

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 Supervised-Point Rendering and Visibility Representation,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Liu, K.C.[Kang-Cheng],
RM3D: Robust Data-Efficient 3D Scene Parsing via Traditional and Learnt 3D Descriptors-Based Semantic Region Merging,
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 BibRef

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. BibRef

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 BibRef

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 Abstraction,
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 BibRef

Wu, J.Q.[Jun-Qi], Yao, W.[Wen], Jia, S.[Shuai], Jiang, T.S.[Ting-Song], Zhou, W.[Weien], 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 BibRef

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 clouds,
CVIU(236), 2023, pp. 103808.
Elsevier DOI 2310
Deep learning, 3D object detection, Point clouds, Transformers, Single-stage detector BibRef

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
BibRef

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:
WWW Link. 2311
BibRef

Zhu, Y.J.[Yi-Jie], Xie, J.M.[Jing-Ming], 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 BibRef

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
BibRef

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 BibRef

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 BibRef

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 2307
BibRef

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 Object Detection,
SPLetters(30), 2023, pp. 798-802.
IEEE DOI 2307
Feature extraction, Transformers, Object detection, Point cloud compression, Estimation, Encoding, transformer BibRef

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.
Elsevier DOI Code:
WWW Link. 2402
LiDAR, 3D object detection, Multi-modal, Point cloud features BibRef

Wang, J.[Jian], Li, F.[Fan], Zhang, X.[Xuchong], Sun, H.B.[Hong-Bin],
Adversarial Obstacle Generation Against LiDAR-Based 3D Object Detection,
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 BibRef

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 BibRef

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 BibRef

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 BibRef

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 BibRef

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


Palmer, P.[Patrick], Krüger, M.[Martin], Schütte, S.[Stefan], Altendorfer, R.[Richard], Adam, G.[Ganesh], Bertram, T.[Torsten],
Lerojd: Lidar Extended Radar-only Object Detection,
ECCV24(LX: 379-396).
Springer DOI 2412
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 .


Last update:Jan 20, 2025 at 11:36:25