Chen, X.[Xujian],
Teoh, E.K.[Eam Khwang],
3D object segmentation using B-Surface,
IVC(23), No. 14, 12 December 2005, pp. 1237-1249.
Elsevier DOI
0601
BibRef
Earlier:
3D growing deformable B-surface model for object detection,
ICARCV04(I: 357-362).
IEEE DOI
0412
Slice by slice.
BibRef
Reisert, M.[Marco],
Burkhardt, H.[Hans],
Complex Derivative Filters,
IP(17), No. 12, December 2008, pp. 2265-2274.
IEEE DOI
0811
BibRef
Reisert, M.[Marco],
Burkhardt, H.[Hans],
Equivariant Holomorphic Filters for Contour Denoising and Rapid Object
Detection,
IP(17), No. 2, February 2008, pp. 190-203.
IEEE DOI
0801
BibRef
Reisert, M.[Marco],
Ronneberger, O.[Olaf],
Burkhardt, H.[Hans],
Holomorphic Filters for Object Detection,
DAGM07(304-313).
Springer DOI
0709
BibRef
And:
A Fast and Reliable Coin Recognition System,
DAGM07(415-424).
Springer DOI
0709
BibRef
Reisert, M.[Marco],
Burkhardt, H.[Hans],
Efficient Tensor Voting with 3D tensorial harmonics,
Tensor08(1-7).
IEEE DOI
0806
BibRef
Reisert, M.[Marco],
Burkhardt, H.[Hans],
Harmonic Filters for Generic Feature Detection in 3D,
DAGM09(131-140).
Springer DOI
0909
See also Harmonic Filters for 3D Multichannel Data: Rotation Invariant Detection of Mitoses in Colorectal Cancer.
BibRef
Reisert, M.[Marco],
Burkhardt, H.[Hans],
Using Irreducible Group Representations for Invariant 3D Shape
Description,
DAGM06(132-141).
Springer DOI
0610
BibRef
And:
Feature Selection for Retrieval Purposes,
ICIAR06(I: 661-672).
Springer DOI
0610
BibRef
Earlier:
Invariant Features for 3D-Data based on Group Integration using
Directional Information and Spherical Harmonic Expansion,
ICPR06(IV: 206-209).
IEEE DOI
0609
BibRef
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
Yang, B.S.[Bi-Sheng],
Dong, Z.[Zhen],
A shape-based segmentation method for mobile laser scanning point
clouds,
PandRS(81), No. 1, July 2013, pp. 19-30.
Elsevier DOI
1306
Point classification; Object segmentation; Mobile laser
scanning; Object extraction
BibRef
Yang, B.S.[Bi-Sheng],
Li, Y.H.[Yu-Hao],
Zou, X.H.[Xiang-Hong],
Dong, Z.[Zhen],
A Marker-free Calibration Method for Mobile Laser Scanning Point Clouds
Correction,
ISPRS20(B2:347-354).
DOI Link
2012
BibRef
Kiforenko, L.[Lilita],
Drost, B.[Bertram],
Tombari, F.[Federico],
Krüger, N.[Norbert],
Buch, A.G.[Anders Glent],
A performance evaluation of point pair features,
CVIU(166), No. 1, 2018, pp. 66-80.
Elsevier DOI
1712
PPF
BibRef
Kiforenko, L.[Lilita],
Buch, A.G.[Anders Glent],
Krüger, N.[Norbert],
Object Detection Using a Combination of Multiple 3D Feature Descriptors,
CVS15(343-353).
Springer DOI
1507
BibRef
Fu, J.S.[Jun-Sheng],
Kämäräinen, J.K.[Joni-Kristian],
Buch, A.G.[Anders Glent],
Krüger, N.[Norbert],
Indoor Objects and Outdoor Urban Scenes Recognition by 3D Visual
Primitives,
BD3DCV14(270-285).
Springer DOI
1504
BibRef
Fehr, D.[Duc],
Beksi, W.J.[William J.],
Zermas, D.[Dimitris],
Papanikolopoulos, N.[Nikolaos],
Covariance based point cloud descriptors for object detection and
recognition,
CVIU(142), No. 1, 2016, pp. 80-93.
Elsevier DOI
1512
RGB-D data
BibRef
Wang, Z.L.[Zi-Lei],
Xiang, D.,
Hou, S.H.[Sai-Hui],
Wu, F.[Feng],
Background-Driven Salient Object Detection,
MultMed(19), No. 4, April 2017, pp. 750-762.
IEEE DOI
1704
Benchmark testing
BibRef
Hou, S.H.[Sai-Hui],
Wang, Z.L.[Zi-Lei],
Wu, F.[Feng],
Deeply Exploit Depth Information for Object Detection,
Robust16(1092-1100)
IEEE DOI
1612
BibRef
Qu, L.,
He, S.,
Zhang, J.,
Tian, J.,
Tang, Y.,
Yang, Q.,
RGBD Salient Object Detection via Deep Fusion,
IP(26), No. 5, May 2017, pp. 2274-2285.
IEEE DOI
1704
BibRef
Wang, A.,
Wang, M.,
RGB-D Salient Object Detection via Minimum Barrier Distance Transform
and Saliency Fusion,
SPLetters(24), No. 5, May 2017, pp. 663-667.
IEEE DOI
1704
Image color analysis
BibRef
Xu, X.Y.[Xiang-Yang],
Li, Y.C.[Yun-Cheng],
Wu, G.S.[Gang-Shan],
Luo, J.B.[Jie-Bo],
Multi-modal deep feature learning for RGB-D object detection,
PR(72), No. 1, 2017, pp. 300-313.
Elsevier DOI
1708
RGB-D, objectness estimation
BibRef
Chen, H.[Hao],
Deng, Y.J.[Yong-Jian],
Li, Y.F.[You-Fu],
Hung, T.Y.[Tzu-Yi],
Lin, G.S.[Guo-Sheng],
RGBD Salient Object Detection via Disentangled Cross-Modal Fusion,
IP(29), 2020, pp. 8407-8416.
IEEE DOI
2008
Image reconstruction, Feature extraction, Object detection,
Topology, Image color analysis, Machine learning,
saliency detection
BibRef
Chen, H.[Hao],
Li, Y.F.[You-Fu],
Su, D.[Dan],
Discriminative Cross-Modal Transfer Learning and Densely Cross-Level
Feedback Fusion for RGB-D Salient Object Detection,
Cyber(50), No. 11, November 2020, pp. 4808-4820.
IEEE DOI
2011
Saliency detection, Object detection, Task analysis, Cognition,
Feature extraction, Fuses, Predictive models,
salient object detection
BibRef
Pahwa, R.S.[Ramanpreet Singh],
Lu, J.,
Jiang, N.,
Ng, T.T.[Tian Tsong],
Do, M.N.[Minh N.],
Locating 3D Object Proposals: A Depth-Based Online Approach,
CirSysVideo(28), No. 3, March 2018, pp. 626-639.
IEEE DOI
1804
computational geometry, image colour analysis,
image registration, image sequences, object detection,
robot vision
BibRef
Xiao, X.,
Zhou, Y.,
Gong, Y.,
RGB-'D' Saliency Detection With Pseudo Depth,
IP(28), No. 5, May 2019, pp. 2126-2139.
IEEE DOI
1903
feature extraction, image colour analysis,
stereo image processing, supervised learning,
salient object detection
BibRef
Huang, R.,
Xing, Y.,
Wang, Z.,
RGB-D Salient Object Detection by a CNN With Multiple Layers Fusion,
SPLetters(26), No. 4, April 2019, pp. 552-556.
IEEE DOI
1903
Saliency detection, Detectors, Training, Computational modeling,
Benchmark testing, Feature extraction, Fuses,
CNN
BibRef
Wang, R.Z.[Run-Zhi],
Wan, W.H.[Wen-Hui],
Wang, Y.K.[Yong-Kang],
Di, K.C.[Kai-Chang],
A New RGB-D SLAM Method with Moving Object Detection for Dynamic
Indoor Scenes,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Li, G.,
Liu, Z.,
Ling, H.,
ICNet: Information Conversion Network for RGB-D Based Salient Object
Detection,
IP(29), 2020, pp. 4873-4884.
IEEE DOI
2003
Feature extraction, Correlation, Fuses, Decoding, Object detection,
Visualization, Convolution, RGB-D based salient object detection,
siamese structure
BibRef
Li, Y.[Ying],
Ma, L.F.[Ling-Fei],
Tan, W.[Weikai],
Sun, C.[Chen],
Cao, D.[Dongpu],
Li, J.[Jonathan],
GRNet: Geometric relation network for 3D object detection from point
clouds,
PandRS(165), 2020, pp. 43-53.
Elsevier DOI
2006
Deep learning, 3D object detection, Point cloud,
Geometric relation, Indoor mapping, RGB-D
BibRef
Yan, L.[Lin],
Liu, K.[Kai],
Belyaev, E.[Evgeny],
Duan, M.[Meiyu],
RTL3D: real-time LIDAR-based 3D object detection with sparse CNN,
IET-CV(14), No. 5, August 2020, pp. 224-232.
DOI Link
2007
collapse 3D to 2D for initial detection.
BibRef
Wang, J.R.[Jia-Rong],
Zhu, M.[Ming],
Wang, B.[Bo],
Sun, D.[Deyao],
Wei, H.[Hua],
Liu, C.J.[Chang-Ji],
Nie, H.T.[Hai-Tao],
KDA3D: Key-Point Densification and Multi-Attention Guidance for 3D
Object Detection,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
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
Zhou, X.F.[Xiao-Fei],
Wen, H.F.[Hong-Fa],
Shi, R.[Ran],
Yin, H.B.[Hai-Bing],
Yan, C.G.[Cheng-Gang],
Depth-guided saliency detection via boundary information,
IVC(103), 2020, pp. 104001.
Elsevier DOI
2011
RGBD, Saliency, Boundary, Depth
BibRef
Wang, X.,
Li, S.,
Chen, C.,
Fang, Y.,
Hao, A.,
Qin, H.,
Data-Level Recombination and Lightweight Fusion Scheme for RGB-D
Salient Object Detection,
IP(30), 2021, pp. 458-471.
IEEE DOI
2012
Object detection, Feature extraction, Semantics, Deep learning,
Estimation, Training, Network architecture,
lightweight designed triple-stream network
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
Xie, Q.[Qian],
Lai, Y.K.[Yu-Kun],
Wu, J.[Jing],
Wang, Z.T.[Zhou-Tao],
Zhang, Y.M.[Yi-Ming],
Xu, K.[Kai],
Wang, J.[Jun],
Vote-Based 3D Object Detection with Context Modeling and SOB-3DNMS,
IJCV(129), No. 6, June 2021, pp. 1857-1874.
Springer DOI
2106
BibRef
Pan, X.R.[Xu-Ran],
Xia, Z.F.[Zhuo-Fan],
Song, S.J.[Shi-Ji],
Li, L.E.[Li Erran],
Huang, G.[Gao],
3D Object Detection with Pointformer,
CVPR21(7459-7468)
IEEE DOI
2111
Solid modeling, Shape, Semantics,
Object detection, Transformers, Pattern recognition
BibRef
An, P.[Pei],
Liang, J.X.[Jun-Xiong],
Yu, K.[Kun],
Fang, B.[Bin],
Ma, J.[Jie],
Deep structural information fusion for 3D object detection on
LiDAR-camera system,
CVIU(214), 2022, pp. 103295.
Elsevier DOI
2112
3D object detection, LiDAR-camera system, Multi-sensor fusion
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
Wu, Y.Q.[Yi-Qiang],
Xiao, W.P.[Wei-Ping],
Liu, C.[Chang],
Gao, J.T.[Jian-Tao],
Sun, J.C.[Jia-Cheng],
Tan, G.Z.[Guo-Zhu],
Li, X.M.[Xiao-Mao],
RE-Det3D: RoI-enhanced 3D object detector,
IVC(121), 2022, pp. 104430.
Elsevier DOI
2205
3D object detection, Point-based method,
Proposal-shape understanding, Tilted sampling, Self-attention,
Plug-and-play module
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
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
Chen, L.H.[Ling-Hao],
Sun, J.M.[Jia-Ming],
Xie, Y.M.[Yi-Ming],
Zhang, S.[Siyu],
Shuai, Q.[Qing],
Jiang, Q.H.[Qin-Hong],
Zhang, G.F.[Guo-Feng],
Bao, H.J.[Hu-Jun],
Zhou, X.W.[Xiao-Wei],
Shape Prior Guided Instance Disparity Estimation for 3D Object
Detection,
PAMI(44), No. 9, September 2022, pp. 5529-5540.
IEEE DOI
2208
BibRef
Earlier: A2, A1, A3, A4, A5, A9, A8, Only:
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided
Instance Disparity Estimation,
CVPR20(10545-10554)
IEEE DOI
2008
Estimation, Object detection, Shape, Solid modeling, Laser radar,
Image reconstruction, Autonomous driving, 3D detection, stereo matching.
Detectors
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
Ma, J.W.[Jia-Wei],
Liang, M.[Min],
Chen, S.L.[Song-Lu],
Chen, F.[Feng],
Tian, S.[Shu],
Qin, J.Y.[Jing-Yan],
Yin, X.C.[Xu-Cheng],
Depth-Guided Progressive Network for Object Detection,
ITS(23), No. 10, October 2022, pp. 19523-19533.
IEEE DOI
2210
Feature extraction, Object detection, Detectors, Interference,
Signal to noise ratio, Semantics, Location awareness, progressive sampling
BibRef
Ji, C.F.[Chao-Feng],
Liu, G.Z.[Gui-Zhong],
Zhao, D.[Dan],
ETS-3D: An Efficient Two-Stage Framework for Stereo 3D Object
Detection,
JVCIR(88), 2022, pp. 103634.
Elsevier DOI
2210
3D Object Detection, Deep Learning, Stereo Matching, Autonomous Driving
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
Liu, N.[Nian],
Zhang, N.[Ni],
Shao, L.[Ling],
Han, J.W.[Jun-Wei],
Learning Selective Mutual Attention and Contrast for RGB-D Saliency
Detection,
PAMI(44), No. 12, December 2022, pp. 9026-9042.
IEEE DOI
2212
BibRef
Earlier: A1, A2, A4, Only:
Learning Selective Self-Mutual Attention for RGB-D Saliency Detection,
CVPR20(13753-13762)
IEEE DOI
2008
Frequency modulation, Salient object detection, RGB-D image,
attention model, contrast, non-local network.
Fuses, Saliency detection, Data models, Task analysis,
Computational modeling, Object detection, Feature extraction
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
Shi, S.S.[Shao-Shuai],
Jiang, L.[Li],
Deng, J.J.[Jia-Jun],
Wang, Z.[Zhe],
Guo, C.X.[Chao-Xu],
Shi, J.P.[Jian-Ping],
Wang, X.G.[Xiao-Gang],
Li, H.S.[Hong-Sheng],
PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector
Representation for 3D Object Detection,
IJCV(131), No. 2, February 2023, pp. 531-551.
Springer DOI
2301
BibRef
Earlier: A1, A5, A2, A4, A6, A7, A8, Only:
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection,
CVPR20(10526-10535)
IEEE DOI
2008
Feature extraction, Proposals,
Encoding, Object detection, Aggregates
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
Zhang, X.Y.[Xin-Yuan],
Han, F.[Fei],
Shen, S.[Shiyang],
Wang, Y.C.[Yi-Cheng],
Xu, S.[Shilong],
Dong, X.[Xiao],
Hu, Y.H.[Yi-Hua],
Target region extraction and segmentation algorithm for reflective
tomography Lidar image,
IET-IPR(17), No. 4, 2023, pp. 1001-1009.
DOI Link
2303
image segmentation, Lidar, reflective tomography, target region extraction
BibRef
Yang, J.[Jihan],
Shi, S.S.[Shao-Shuai],
Wang, Z.[Zhe],
Li, H.S.[Hong-Sheng],
Qi, X.J.[Xiao-Juan],
ST3D++: Denoised Self-Training for Unsupervised Domain Adaptation on
3D Object Detection,
PAMI(45), No. 5, May 2023, pp. 6354-6371.
IEEE DOI
2304
BibRef
Earlier:
ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object
Detection,
CVPR21(10363-10373)
IEEE DOI
2111
Object detection, Data models,
Training, Solid modeling, Task analysis, Detectors, autonomous driving.
Codes, Pipelines, Detectors.
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
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
Sheng, H.[Hualian],
Cai, S.[Sijia],
Zhao, N.[Na],
Deng, B.[Bing],
Huang, J.Q.[Jian-Qiang],
Hua, X.S.[Xian-Sheng],
Zhao, M.J.[Min-Jian],
Lee, G.H.[Gim Hee],
Rethinking IoU-based Optimization for Single-stage 3D Object Detection,
ECCV22(IX:544-561).
Springer DOI
2211
BibRef
Huang, Y.[Yaomin],
Liu, X.[Xinmei],
Zhu, Y.C.[Yi-Chen],
Xu, Z.Y.[Zhi-Yuan],
Shen, C.M.[Chao-Min],
Che, Z.P.[Zheng-Ping],
Zhang, G.X.[Gui-Xu],
Peng, Y.X.[Ya-Xin],
Feng, F.F.[Fei-Fei],
Tang, J.[Jian],
Label-Guided Auxiliary Training Improves 3D Object Detector,
ECCV22(IX:684-700).
Springer DOI
2211
BibRef
Chen, Y.T.[Yi-Ting],
Shi, J.H.[Jing-Hao],
Ye, Z.L.[Ze-Lin],
Mertz, C.[Christoph],
Ramanan, D.[Deva],
Kong, S.[Shu],
Multimodal Object Detection via Probabilistic Ensembling,
ECCV22(IX:139-158).
Springer DOI
2211
BibRef
Liu, Y.F.[Ying-Fei],
Wang, T.C.[Tian-Cai],
Zhang, X.Y.[Xiang-Yu],
Sun, J.[Jian],
PETR: Position Embedding Transformation for Multi-View 3D Object
Detection,
ECCV22(XXVII:531-548).
Springer DOI
2211
BibRef
Chen, Z.[Zehui],
Li, Z.Y.[Zhen-Yu],
Zhang, S.Q.[Shi-Quan],
Fang, L.J.[Liang-Ji],
Jiang, Q.H.[Qin-Hong],
Zhao, F.[Feng],
Deformable Feature Aggregation for Dynamic Multi-modal 3D Object
Detection,
ECCV22(VIII:628-644).
Springer DOI
2211
BibRef
Adam, M.G.[Michael G.],
Piccolrovazzi, M.[Martin],
Eger, S.[Sebastian],
Steinbach, E.[Eckehard],
Bounding Box Disparity: 3D Metrics for Object Detection with Full
Degree of Freedom,
ICIP22(1491-1495)
IEEE DOI
2211
Measurement, Closed-form solutions, Object detection, Libraries,
metric, object detection, 3D bounding box, intersection over union,
volume-to-volume distance
BibRef
Shi, G.S.[Guang-Sheng],
Li, R.F.[Rui-Feng],
Ma, C.[Chao],
PillarNet: Real-Time and High-Performance Pillar-Based 3D Object
Detection,
ECCV22(X:35-52).
Springer DOI
2211
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
Rukhovich, D.[Danila],
Vorontsova, A.[Anna],
Konushin, A.[Anton],
FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection,
ECCV22(X:477-493).
Springer DOI
2211
BibRef
Li, H.[Hao],
Zhang, Z.[Zehan],
Zhao, X.[Xian],
Wang, Y.L.[Yu-Long],
Shen, Y.X.[Yu-Xi],
Pu, S.L.[Shi-Liang],
Mao, H.[Hui],
Enhancing Multi-modal Features Using Local Self-attention for 3D Object
Detection,
ECCV22(X:532-549).
Springer DOI
2211
BibRef
Wang, T.Y.[Tian-Yu],
Liu, M.M.[Miao-Miao],
Ng, K.S.[Kee Siong],
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene
Decomposition,
ECCV22(XXIII:120-135).
Springer DOI
2211
BibRef
Li, X.[Xin],
Shi, B.[Botian],
Hou, Y.[Yuenan],
Wu, X.J.[Xing-Jiao],
Ma, T.L.[Tian-Long],
Li, Y.K.[Yi-Kang],
He, L.[Liang],
Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object
Detection,
ECCV22(XXXVIII:691-707).
Springer DOI
2211
BibRef
Duan, Y.[Yao],
Zhu, C.Y.[Chen-Yang],
Lan, Y.Q.[Yu-Qing],
Yi, R.[Renjiao],
Liu, X.[Xinwang],
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
Zeng, Y.[Yihan],
Zhang, D.[Da],
Wang, C.[Chunwei],
Miao, Z.W.[Zhen-Wei],
Liu, T.[Ting],
Zhan, X.[Xin],
Hao, D.[Dayang],
Ma, C.[Chao],
LIFT: Learning 4D LiDAR Image Fusion Transformer for 3D Object
Detection,
CVPR22(17151-17160)
IEEE DOI
2210
Training, Laser radar, Object detection, Transformers, Cameras,
Sensors, Navigation and autonomous driving, 3D from multi-view and sensors
BibRef
Wang, H.Y.[Hai-Yang],
Shi, S.[Shaoshuai],
Yang, Z.[Ze],
Fang, R.[Rongyao],
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
Li, Y.W.[Yan-Wei],
Qi, X.J.[Xiao-Juan],
Chen, Y.[Yukang],
Wang, L.W.[Li-Wei],
Li, Z.[Zeming],
Sun, J.[Jian],
Jia, J.Y.[Jia-Ya],
Voxel Field Fusion for 3D Object Detection,
CVPR22(1110-1119)
IEEE DOI
2210
Bridges, Codes, Fuses, Computational modeling, Object detection,
Recognition: detection, categorization, retrieval,
3D from multi-view and sensors
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
Zheng, Y.[Yu],
Duan, Y.[Yueqi],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Tian, Q.[Qi],
HyperDet3D: Learning a Scene-conditioned 3D Object Detector,
CVPR22(5575-5584)
IEEE DOI
2210
Face recognition, Object detection, Detectors, Benchmark testing,
Libraries, 3D from multi-view and sensors, retrieval
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
Guo, X.Y.[Xiao-Yang],
Shi, S.S.[Shao-Shuai],
Wang, X.G.[Xiao-Gang],
Li, H.S.[Hong-Sheng],
LIGA-Stereo: Learning LiDAR Geometry Aware Representations for
Stereo-based 3D Detector,
ICCV21(3133-3143)
IEEE DOI
2203
Geometry, Point cloud compression, Solid modeling, Laser radar,
Semantics, Detectors, Detection and localization in 2D and 3D,
3D from multiview and other sensors
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
Mao, J.G.[Jia-Geng],
Xue, Y.J.[Yu-Jing],
Niu, M.Z.[Min-Zhe],
Bai, H.Y.[Hao-Yue],
Feng, J.S.[Jia-Shi],
Liang, X.D.[Xiao-Dan],
Xu, H.[Hang],
Xu, C.J.[Chun-Jing],
Voxel Transformer for 3D Object Detection,
ICCV21(3144-3153)
IEEE DOI
2203
Point cloud compression, Location awareness, Detectors,
Object detection,
Vision for robotics and autonomous vehicles
BibRef
Sun, J.M.[Jia-Ming],
Xie, Y.M.[Yi-Ming],
Zhang, S.[Siyu],
Chen, L.H.[Ling-Hao],
Zhang, G.F.[Guo-Feng],
Bao, H.J.[Hu-Jun],
Zhou, X.W.[Xiao-Wei],
You Don't Only Look Once: Constructing Spatial-Temporal Memory for
Integrated 3D Object Detection and Tracking,
ICCV21(3265-3174)
IEEE DOI
2203
Memory management, Pipelines, Object detection, Detectors,
Search problems, Trajectory,
Vision for robotics and autonomous vehicles
BibRef
Rao, Y.M.[Yong-Ming],
Liu, B.[Benlin],
Wei, Y.[Yi],
Lu, J.W.[Ji-Wen],
Hsieh, C.J.[Cho-Jui],
Zhou, J.[Jie],
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and
Randomized Layouts for 3D Object Detection,
ICCV21(3263-3272)
IEEE DOI
2203
Solid modeling, Semantics, Layout, Training data, Object detection,
Benchmark testing, Detection and localization in 2D and 3D,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Liang, H.[Hanxue],
Jiang, C.[Chenhan],
Feng, D.P.[Da-Peng],
Chen, X.[Xin],
Xu, H.[Hang],
Liang, X.D.[Xiao-Dan],
Zhang, W.[Wei],
Li, Z.G.[Zhen-Guo],
Van Gool, L.J.[Luc J.],
Exploring Geometry-aware Contrast and Clustering Harmonization for
Self-supervised 3D Object Detection,
ICCV21(3273-3282)
IEEE DOI
2203
Representation learning, Roads, Semantics, Pipelines, Prototypes,
Object detection, Detection and localization in 2D and 3D,
Vision for robotics and autonomous vehicles
BibRef
Xie, Q.[Qian],
Lai, Y.K.[Yu-Kun],
Wu, J.[Jing],
Wang, Z.[Zhoutao],
Lu, D.[Dening],
Wei, M.Q.[Ming-Qiang],
Wang, J.[Jun],
VENet: Voting Enhancement Network for 3D Object Detection,
ICCV21(3692-3701)
IEEE DOI
2203
Object detection, Detectors, Benchmark testing, Feature extraction,
Sun, Detection and localization in 2D and 3D,
Vision for robotics and autonomous vehicles
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
Rukhovich, D.[Danila],
Vorontsova, A.[Anna],
Konushin, A.[Anton],
ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View
General-Purpose 3D Object Detection,
WACV22(1265-1274)
IEEE DOI
2202
Training, Convolutional codes,
Object detection, Benchmark testing, Deep Learning
BibRef
Xu, H.Y.[Hong-Yi],
Liu, F.Q.[Feng-Qi],
Zhou, Q.Y.[Qian-Yu],
Hao, J.K.[Jin-Kun],
Cao, Z.J.[Zhi-Jie],
Feng, Z.Y.[Zheng-Yang],
Ma, L.Z.[Li-Zhuang],
Semi-Supervised 3d Object Detection Via Adaptive Pseudo-Labeling,
ICIP21(3183-3187)
IEEE DOI
2201
Annotations, Filtering, Image processing, Object detection,
Benchmark testing, 3D object detection, point clouds, semi-supervised learning
BibRef
Yun, P.[Peng],
Cen, J.[Jun],
Liu, M.[Ming],
Conflicts between Likelihood and Knowledge Distillation in Task
Incremental Learning for 3D Object Detection,
3DV21(575-585)
IEEE DOI
2201
Image edge detection, Semantics, Estimation, Object detection,
Task analysis, Autonomous vehicles, Robotics,
High level representation of 3D data
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
Park, W.[Won],
Liu, N.[Nan],
Chen, Q.A.[Qi Alfred],
Mao, Z.M.[Z. Morley],
Sensor Adversarial Traits: Analyzing Robustness of 3D Object
Detection Sensor Fusion Models,
ICIP21(484-488)
IEEE DOI
2201
Training, Solid modeling, Analytical models, Laser radar,
Object detection, Sensor fusion, Adversarial examples, multimodal,
sensor fusion
BibRef
Lei, J.J.[Jian-Jun],
Guo, T.[Tingyi],
Peng, B.[Bo],
Yu, C.B.[Chuan-Bo],
Depth-Assisted Joint Detection Network for Monocular 3d Object
Detection,
ICIP21(2204-2208)
IEEE DOI
2201
Location awareness, Image processing, Object detection,
Streaming media, Benchmark testing, 3D object detection,
orientation-embedded NMS
BibRef
Liu, H.Z.[Hai-Zhuang],
Ma, H.M.[Hui-Min],
Chen, Y.X.[Yan-Xian],
Li, X.[Xi],
Hu, T.Y.[Tian-Yu],
PLNL-3DSSD: Part-Aware 3D Single Stage Detector Using Local and
Non-Local Attention,
ICIP21(3148-3152)
IEEE DOI
2201
Image coding, Semantics, Detectors, Object detection,
Benchmark testing, 3D object detection, local attention,
3D single-stage detector
BibRef
Bhattacharyya, P.[Prarthana],
Huang, C.J.[Cheng-Jie],
Czarnecki, K.[Krzysztof],
SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection,
AVVision21(3022-3031)
IEEE DOI
2112
Convolutional codes, Solid modeling,
Computational modeling, Neural networks, Detectors, Object detection
BibRef
Meyer, M.[Michael],
Kuschk, G.[Georg],
Tomforde, S.[Sven],
Graph Convolutional Networks for 3D Object Detection on Radar Data,
AVVision21(3053-3062)
IEEE DOI
2112
Tensors, Laser radar, Convolution,
Radar detection, Object detection, Feature extraction
BibRef
Wang, Z.J.[Ze-Jie],
Zhao, Z.[Zhen],
Jin, Z.[Zhao],
Che, Z.P.[Zheng-Ping],
Tang, J.[Jian],
Shen, C.M.[Chao-Min],
Peng, Y.X.[Ya-Xin],
Multi-Stage Fusion for Multi-Class 3D Lidar Detection,
AVVision21(3113-3121)
IEEE DOI
2112
Laser radar, Semantics,
Object detection, Logic gates, Feature extraction, Cameras
BibRef
Chai, Y.N.[Yu-Ning],
Sun, P.[Pei],
Ngiam, J.[Jiquan],
Wang, W.[Weiyue],
Caine, B.[Benjamin],
Vasudevan, V.[Vijay],
Zhang, X.[Xiao],
Anguelov, D.[Dragomir],
To the Point: Efficient 3D Object Detection in the Range Image with
Graph Convolution Kernels,
CVPR21(15995-16004)
IEEE DOI
2111
Convolution, Computational modeling,
Robot kinematics, Object detection, Network architecture, Transformers
BibRef
Noh, J.[Jongyoun],
Lee, S.H.[Sang-Hoon],
Ham, B.[Bumsub],
HVPR: Hybrid Voxel-Point Representation for Single-stage 3D Object
Detection,
CVPR21(14600-14609)
IEEE DOI
2111
Solid modeling,
Computational modeling, Memory management, Object detection, Memory modules
BibRef
Wang, H.[He],
Cong, Y.Z.[Ye-Zhen],
Litany, O.[Or],
Gao, Y.[Yue],
Guibas, L.J.[Leonidas J.],
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object
Detection,
CVPR21(14610-14619)
IEEE DOI
2111
Location awareness, Training,
Filtering, Estimation, Object detection, Detectors
BibRef
Wang, C.W.[Chun-Wei],
Ma, C.[Chao],
Zhu, M.[Ming],
Yang, X.K.[Xiao-Kang],
PointAugmenting: Cross-Modal Augmentation for 3D Object Detection,
CVPR21(11789-11798)
IEEE DOI
2111
Training, Adaptation models, Solid modeling,
Laser radar, Object detection, Detectors
BibRef
Chen, H.S.[Han-Sheng],
Huang, Y.[Yuyao],
Tian, W.[Wei],
Gao, Z.[Zhong],
Xiong, L.[Lu],
MonoRUn: Monocular 3D Object Detection by Reconstruction and
Uncertainty Propagation,
CVPR21(10374-10383)
IEEE DOI
2111
Location awareness, Geometry, Training,
Uncertainty, Tracking, Object detection
BibRef
Miao, Z.W.[Zhen-Wei],
Chen, J.K.[Ji-Kai],
Pan, H.Y.[Hong-Yu],
Zhang, R.[Ruiwen],
Liu, K.X.[Kai-Xuan],
Hao, P.H.[Pei-Han],
Zhu, J.[Jun],
Wang, Y.[Yang],
Zhan, X.[Xin],
PVGNet: A Bottom-Up One-Stage 3D Object Detector with Integrated
Multi-Level Features,
CVPR21(3278-3287)
IEEE DOI
2111
Training, Laser radar,
Quantization (signal), Merging, Object detection, Detectors
BibRef
Yang, Z.T.[Ze-Tong],
Zhou, Y.[Yin],
Chen, Z.F.[Zhi-Feng],
Ngiam, J.Q.[Ji-Quan],
3D-MAN: 3D Multi-frame Attention Network for Object Detection,
CVPR21(1863-1872)
IEEE DOI
2111
Fuses, Aggregates, Object detection, Detectors, Feature extraction
BibRef
Liang, Z.D.[Zhi-Dong],
Zhang, Z.[Zehan],
Zhang, M.[Ming],
Zhao, X.[Xian],
Pu, S.L.[Shi-Liang],
RangeIoUDet: Range Image based Real-Time 3D Object Detector Optimized
by Intersection over Union,
CVPR21(7136-7145)
IEEE DOI
2111
Solid modeling, Laser radar,
Convolution, Object detection, Detectors, Predictive models
BibRef
Aghdam, H.H.[Hamed H.],
Heravi, E.J.[Elnaz J.],
Demilew, S.S.[Selameab S.],
Laganiere, R.[Robert],
RAD: Realtime and Accurate 3D Object Detection on Embedded Systems,
WAD21(2869-2877)
IEEE DOI
2109
Measurement, Embedded computing,
Computational modeling, Neural networks, Detectors, Object detection
BibRef
Laddha, A.[Ankit],
Gautam, S.[Shivam],
Palombo, S.[Stefan],
Pandey, S.[Shreyash],
Vallespi-Gonzalez, C.[Carlos],
MVFuseNet: Improving End-to-End Object Detection and Motion
Forecasting through Multi-View Fusion of LiDAR Data,
WAD21(2859-2868)
IEEE DOI
2109
Laser radar, Object detection,
Real-time systems, Pattern recognition, Forecasting
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.X.[Yan-Xian],
Ma, H.M.[Hui-Min],
Li, X.[Xi],
Luo, X.[Xiong],
S-VoteNet: Deep Hough Voting with Spherical Proposal for 3D Object
Detection,
ICPR21(5161-5167)
IEEE DOI
2105
Location awareness, Estimation,
Detectors, Object detection, Size measurement, Loss measurement
BibRef
Yang, Z.[Zhen],
Zhang, C.[Chi],
Guo, H.M.[Hui-Ming],
Zhang, Z.X.[Zhao-Xiang],
Manual-Label Free 3D Detection via An Open-Source Simulator,
ICPR21(3272-3279)
IEEE DOI
2105
Training, Solid modeling, Adaptation models,
Laser radar, Detectors, Manuals
BibRef
Griffiths, D.[David],
Boehm, J.[Jan],
Ritschel, T.[Tobias],
Finding Your (3D) Center: 3d Object Detection Using a Learned Loss,
ECCV20(XVIII:70-85).
Springer DOI
2012
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
Yoo, J.H.[Jin Hyeok],
Kim, Y.[Yecheol],
Kim, J.[Jisong],
Choi, J.W.[Jun Won],
3D-CVF: Generating Joint Camera and Lidar Features Using Cross-view
Spatial Feature Fusion for 3D Object Detection,
ECCV20(XXVII:720-736).
Springer DOI
2011
BibRef
Cheng, S.Y.[Shu-Yang],
Leng, Z.Q.[Zhao-Qi],
Cubuk, E.D.[Ekin Dogus],
Zoph, B.[Barret],
Bai, C.Y.[Chun-Yan],
Ngiam, J.Q.[Ji-Quan],
Song, Y.[Yang],
Caine, B.[Benjamin],
Vasudevan, V.[Vijay],
Li, C.C.[Cong-Cong],
Le, Q.V.[Quoc V.],
Shlens, J.[Jonathon],
Anguelov, D.[Dragomir],
Improving 3D Object Detection Through Progressive Population Based
Augmentation,
ECCV20(XXI:279-294).
Springer DOI
2011
BibRef
Zheng, Y.[Yu],
Zhang, D.Y.[Dan-Yang],
Xie, S.[Sinan],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Rotation-Robust Intersection over Union for 3d Object Detection,
ECCV20(XX:464-480).
Springer DOI
2011
BibRef
Murez, Z.[Zak],
van As, T.[Tarrence],
Bartolozzi, J.[James],
Sinha, A.[Ayan],
Badrinarayanan, V.[Vijay],
Rabinovich, A.[Andrew],
Atlas: End-to-end 3d Scene Reconstruction from Posed Images,
ECCV20(VII:414-431).
Springer DOI
2011
Without constructing depth maps.
BibRef
Gwak, J.Y.[Jun-Young],
Choy, C.[Christopher],
Savarese, S.[Silvio],
Generative Sparse Detection Networks for 3d Single-shot Object
Detection,
ECCV20(IV:297-313).
Springer DOI
2011
BibRef
Zhang, Z.W.[Zai-Wei],
Sun, B.[Bo],
Yang, H.T.[Hai-Tao],
Huang, Q.X.[Qi-Xing],
H3dnet: 3d Object Detection Using Hybrid Geometric Primitives,
ECCV20(XII: 311-329).
Springer DOI
2010
BibRef
Yang, Z.,
Sun, Y.,
Liu, S.,
Jia, J.,
3DSSD: Point-Based 3D Single Stage Object Detector,
CVPR20(11037-11045)
IEEE DOI
2008
Feature extraction, Proposals,
Object detection, Detectors, Semantics
BibRef
Tu, J.,
Ren, M.,
Manivasagam, S.,
Liang, M.,
Yang, B.,
Du, R.,
Cheng, F.,
Urtasun, R.,
Physically Realizable Adversarial Examples for LiDAR Object Detection,
CVPR20(13713-13722)
IEEE DOI
2008
Laser radar, Detectors,
Autonomous vehicles, Solid modeling, Laser theory
BibRef
He, C.,
Zeng, H.,
Huang, J.,
Hua, X.,
Zhang, L.,
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
Piao, Y.,
Rong, Z.,
Zhang, M.,
Ren, W.,
Lu, H.,
A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D
Salient Object Detection,
CVPR20(9057-9066)
IEEE DOI
2008
Saliency detection, Bridges, Testing, Object detection,
Knowledge engineering, Training
BibRef
Xie, Q.,
Lai, Y.,
Wu, J.,
Wang, Z.,
Zhang, Y.,
Xu, K.,
Wang, J.,
MLCVNet: Multi-Level Context VoteNet for 3D Object Detection,
CVPR20(10444-10453)
IEEE DOI
2008
Object detection, Feature extraction, Task analysis, Machine learning
BibRef
Chabra, R.[Rohan],
Lenssen, J.E.[Jan E.],
Ilg, E.[Eddy],
Schmidt, T.[Tanner],
Straub, J.[Julian],
Lovegrove, S.J.[Steven J.],
Newcombe, R.A.[Richard A.],
Deep Local Shapes: Learning Local SDF Priors for Detailed 3D
Reconstruction,
ECCV20(XXIX: 608-625).
Springer DOI
2010
BibRef
Rünz, M.,
Li, K.,
Tang, M.,
Ma, L.,
Kong, C.,
Schmidt, T.,
Reid, I.,
Agapito, L.,
Straub, J.,
Lovegrove, S.J.,
Newcombe, R.A.,
FroDO: From Detections to 3D Objects,
CVPR20(14708-14717)
IEEE DOI
2008
Shape, Decoding, Image reconstruction,
Optimization, Simultaneous localization and mapping
BibRef
Najibi, M.,
Lai, G.,
Kundu, A.,
Lu, Z.,
Rathod, V.,
Funkhouser, T.,
Pantofaru, C.,
Ross, D.,
Davis, L.S.,
Fathi, A.,
DOPS: Learning to Detect 3D Objects and Predict Their 3D Shapes,
CVPR20(11910-11919)
IEEE DOI
2008
Shape, Object detection,
Laser radar, Training, Pipelines
BibRef
Vora, S.,
Lang, A.H.,
Helou, B.,
Beijbom, O.,
PointPainting: Sequential Fusion for 3D Object Detection,
CVPR20(4603-4611)
IEEE DOI
2008
Laser radar, Image segmentation,
Semantics, Object detection, Pipeline processing, Cameras
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
Peng, W.,
Pan, H.,
Liu, H.,
Sun, Y.,
IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision
for Autonomous Driving,
CVPR20(13012-13021)
IEEE DOI
2008
Object detection, Laser radar,
Estimation, Cameras, Stereo vision
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
Fu, K.,
Fan, D.,
Ji, G.,
Zhao, Q.,
JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for
RGB-D Salient Object Detection,
CVPR20(3049-3059)
IEEE DOI
2008
Feature extraction, Adaptation models, Object detection,
Training, Robustness, Decoding
BibRef
Zhang, M.,
Ren, W.,
Piao, Y.,
Rong, Z.,
Lu, H.,
Select, Supplement and Focus for RGB-D Saliency Detection,
CVPR20(3469-3478)
IEEE DOI
2008
Feature extraction, Saliency detection, Image edge detection,
Task analysis, Fuses, Object detection
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
Shen, X.,
Stamos, I.,
Frustum VoxNet for 3D object detection from RGB-D or Depth images,
WACV20(1687-1695)
IEEE DOI
2006
Object detection, Training, Robots, Proposals, Sensors
BibRef
Tang, Y.S.,
Lee, G.H.,
Transferable Semi-Supervised 3D Object Detection From RGB-D Data,
ICCV19(1931-1940)
IEEE DOI
2004
image classification, image colour analysis, object detection,
stereo image processing, supervised learning, Estimation
BibRef
Lang, A.H.[Alex H.],
Vora, S.[Sourabh],
Caesar, H.[Holger],
Zhou, L.[Lubing],
Yang, J.[Jiong],
Beijbom, O.[Oscar],
PointPillars: Fast Encoders for Object Detection From Point Clouds,
CVPR19(12689-12697).
IEEE DOI
2002
BibRef
Lin, W.,
Chen, Y.,
Wang, C.,
Li, J.,
Using Edgeconv to Improve 3d Object Detection From RGB-D Data,
Indoor3D19(835-839).
DOI Link
1912
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
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
Hu, N.[Nan],
Ma, H.M.[Hui-Min],
Le, C.[Chao],
Shao, X.H.[Xue-Hui],
Multi-Modal Feature Fusion Network for Ghost Imaging Object Detection,
ICIP18(351-355)
IEEE DOI
1809
Only low resolution, depth data. Imaging, Feature extraction,
Streaming media, Object detection,
BibRef
Zheng, T.,
Chen, C.,
Yuan, J.,
Li, B.,
Ren, K.,
PointCloud Saliency Maps,
ICCV19(1598-1606)
IEEE DOI
2004
Code, Saliency.
WWW Link. convolutional neural nets, image classification,
image representation, image segmentation, object detection, DGCNN,
Predictive models
BibRef
Zhang, Z.,
Hua, B.,
Yeung, S.,
ShellNet: Efficient Point Cloud Convolutional Neural Networks Using
Concentric Shells Statistics,
ICCV19(1607-1616)
IEEE DOI
2004
convolutional neural nets, feature extraction,
image classification, image representation, image segmentation,
Semantics
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
Yin, K.,
Liu, S.,
Liu, R.,
Chen, Y.,
Shen, K.,
Cross Modal Multiscale Fusion Net for Real-time RGB-D Detection,
ICPR18(2386-2391)
IEEE DOI
1812
convolution, feature extraction, feedforward neural nets,
image colour analysis, object detection, sensor fusion,
Merging
BibRef
Qi, C.R.,
Liu, W.,
Wu, C.,
Su, H.,
Guibas, L.J.,
Frustum PointNets for 3D Object Detection from RGB-D Data,
CVPR18(918-927)
IEEE DOI
1812
Object detection, Proposals, Image segmentation, Detectors
BibRef
Guo, L.[Lin],
Fan, G.L.[Guo-Liang],
Sheng, W.H.[Wei-Hua],
Robust object detection by cuboid matching with local plane
optimization in indoor RGB-D images,
VCIP17(1-4)
IEEE DOI
1804
geometry, image colour analysis, object detection, optimisation,
cuboid candidates, cuboid initialization,
indoor scene
BibRef
Lahoud, J.,
Ghanem, B.,
2D-Driven 3D Object Detection in RGB-D Images,
ICCV17(4632-4640)
IEEE DOI
1802
image colour analysis, learning (artificial intelligence),
multilayer perceptrons, object detection, search problems,
BibRef
Audet, F.[François],
Allili, M.S.[Mohand Said],
Cretu, A.M.[Ana-Maria],
Salient Object Detection in Images by Combining Objectness Clues in the
RGBD Space,
ICIAR17(247-255).
Springer DOI
1706
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
Wang, S.T.[Song-Tao],
Zhou, Z.[Zhen],
Qu, H.B.[Han-Bing],
Li, B.[Bin],
Visual Saliency Detection for RGB-D Images with Generative Model,
ACCV16(V: 20-35).
Springer DOI
1704
BibRef
Peng, H.[Houwen],
Li, B.[Bing],
Xiong, W.H.[Wei-Hua],
Hu, W.M.[Wei-Ming],
Ji, R.R.[Rong-Rong],
RGBD Salient Object Detection: A Benchmark and Algorithms,
ECCV14(III: 92-109).
Springer DOI
1408
BibRef
Ren, Z.[Zhile],
Sudderth, E.B.[Erik B.],
3D Object Detection with Latent Support Surfaces,
CVPR18(937-946)
IEEE DOI
1812
BibRef
Earlier:
Three-Dimensional Object Detection and Layout Prediction Using Clouds
of Oriented Gradients,
CVPR16(1525-1533)
IEEE DOI
1612
Object detection, Feature extraction, Solid modeling, Shape, Proposals
BibRef
Shigematsu, R.,
Feng, D.,
You, S.,
Barnes, N.[Nick],
Learning RGB-D Salient Object Detection Using Background Enclosure,
Depth Contrast, and Top-Down Features,
CogCV17(2749-2757)
IEEE DOI
1802
Feature extraction, Histograms,
Image color analysis, Microprocessors, Object detection, Visualization
BibRef
Feng, D.,
Barnes, N.,
You, S.,
HOSO: Histogram of Surface Orientation for RGB-D Salient Object
Detection,
DICTA17(1-8)
IEEE DOI
1804
graph theory, image colour analysis,
object detection, HOSO, KDF, RGB-D data, RGB-D saliency,
BibRef
Feng, D.,
Barnes, N.[Nick],
You, S.,
McCarthy, C.[Chris],
Local Background Enclosure for RGB-D Salient Object Detection,
CVPR16(2343-2350)
IEEE DOI
1612
BibRef
Chandra, S.[Siddhartha],
Chrysos, G.G.[Grigorios G.],
Kokkinos, I.[Iasonas],
Surface Based Object Detection in RGBD Images,
BMVC15(xx-yy).
DOI Link
1601
BibRef
Liu, W.[Wei],
Ji, R.R.[Rong-Rong],
Li, S.[Shaozi],
Towards 3D object detection with bimodal deep Boltzmann machines over
RGBD imagery,
CVPR15(3013-3021)
IEEE DOI
1510
BibRef
Song, S.[Shuran],
Xiao, J.X.[Jian-Xiong],
Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images,
CVPR16(808-816)
IEEE DOI
1612
BibRef
Earlier:
Sliding Shapes for 3D Object Detection in Depth Images,
ECCV14(VI: 634-651).
Springer DOI
1408
BibRef
Knopp, J.[Jan],
Prasad, M.[Mukta],
Van Gool, L.J.[Luc J.],
Scene Cut:
Class-Specific Object Detection and Segmentation in 3D Scenes,
3DIMPVT11(180-187).
IEEE DOI
1109
See also Orientation invariant 3D object classification using Hough transform based methods.
BibRef
Monroy, A.[Antonio],
Eigenstetter, A.[Angela],
Ommer, B.[Bjorn],
Beyond straight lines: Object detection using curvature,
ICIP11(3561-3564).
IEEE DOI
1201
BibRef
Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Range and Color, RGB-D Segmentation and Analysis .