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DOI Link A method for determining the three-dimensional locations of roadside
features appearing on multiple sequential images captured using a
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Ishii, Y.[Yoshinori],
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IVC(74), 2018, pp. 1-9.
Elsevier DOI
1806
Image analysis, Vegetation detection, Roadside maintenance,
Deep learning, Convolutional neural networks
BibRef
Mao, J.[Jia],
Hong, D.[Dou],
Wang, X.[Xi],
Hsu, C.H.[Ching-Hsien],
Shanthini, A.,
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Chen, C.C.[Chong-Cheng],
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Automatic Extraction of Roadside Traffic Facilities From Mobile Laser
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ITS(22), No. 4, April 2021, pp. 1964-1980.
IEEE DOI
2104
Feature extraction, Machine learning,
Semantics, Automobiles, Solid modeling, Biological system modeling,
normalized cut
See also Individual Tree Extraction from Urban Mobile Laser Scanning Point Clouds Using Deep Pointwise Direction Embedding.
BibRef
Verma, D.[Deepank],
Mumm, O.[Olaf],
Carlow, V.M.[Vanessa Miriam],
Identifying Streetscape Features Using VHR Imagery and Deep Learning
Applications,
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Wang, Z.Y.[Zi-Yang],
Yang, L.[Lin],
Sheng, Y.[Yehua],
Shen, M.[Mi],
Pole-Like Objects Segmentation and Multiscale Classification-Based
Fusion from Mobile Point Clouds in Road Scenes,
RS(13), No. 21, 2021, pp. xx-yy.
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2112
BibRef
Li, G.N.[Guan-Nan],
Lu, X.[Xiu],
Lin, B.X.[Bing-Xian],
Zhou, L.C.[Liang-Chen],
Lv, G.N.[Guo-Nian],
Automatic Positioning of Street Objects Based on Self-Adaptive
Constrained Line of Bearing from Street-View Images,
IJGI(11), No. 4, 2022, pp. xx-yy.
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2205
BibRef
Tang, Q.[Quan],
Liu, F.G.[Fa-Gui],
Jiang, J.[Jun],
Zhang, Y.[Yu],
EPRNet: Efficient Pyramid Representation Network for Real-Time Street
Scene Segmentation,
ITS(23), No. 7, July 2022, pp. 7008-7016.
IEEE DOI
2207
Convolutional codes, Real-time systems, Semantics, Kernel, Encoding,
Computational modeling, Image segmentation,
intelligent vehicles
BibRef
Fang, L.[Lina],
You, Z.L.[Zhi-Long],
Shen, G.X.[Gui-Xi],
Chen, Y.P.[Yi-Ping],
Li, J.R.[Jiang-Rong],
A joint deep learning network of point clouds and multiple views for
roadside object classification from lidar point clouds,
PandRS(193), 2022, pp. 115-136.
Elsevier DOI
2210
Mobile laser scanning systems, Point cloud classification,
Multiview images, Deep learning, Attention mechanism
BibRef
Pechinger, M.[Mathias],
Schröer, G.[Guido],
Bogenberger, K.[Klaus],
Markgraf, C.[Carsten],
Roadside Infrastructure Support for Urban Automated Driving,
ITS(24), No. 10, October 2023, pp. 10643-10652.
IEEE DOI
2310
BibRef
Wang, T.H.[Ting-Han],
Luo, Y.[Yugong],
Liu, J.X.[Jin-Xin],
Chen, R.[Rui],
Li, K.Q.[Ke-Qiang],
End-to-End Self-Driving Approach Independent of Irrelevant Roadside
Objects With Auto-Encoder,
ITS(23), No. 1, January 2022, pp. 641-650.
IEEE DOI
2201
Feature extraction, Training, Task analysis, Roads, Decision making,
Autonomous vehicles, Neural networks, End-to-end self-driving,
irrelevant features
BibRef
Zhang, K.[Kunai],
Liu, Y.H.[Ya-Hui],
Zhang, W.Q.[Wei-Qiang],
Liu, S.S.[Shao-Shan],
p-Learner: A Lifelong Roadside Learning Framework for Infrastructure
Augmented Autonomous Driving,
Computer(55), No. 6, June 2022, pp. 30-39.
IEEE DOI
2206
Road traffic, Vehicle safety, Autonomous vehicles
BibRef
Shi, H.[Hao],
Pang, C.[Chengshan],
Zhang, J.M.[Jia-Ming],
Yang, K.L.[Kai-Lun],
Wu, Y.H.[Yu-Hao],
Ni, H.J.[Hua-Jian],
Lin, Y.[Yining],
Stiefelhagen, R.[Rainer],
Wang, K.W.[Kai-Wei],
CoBEV: Elevating Roadside 3D Object Detection With Depth and Height
Complementarity,
IP(33), 2024, pp. 5424-5439.
IEEE DOI
2410
Cameras, Feature extraction, Object detection, Detectors, Accuracy,
Robustness, Roadside 3D object detection, autonomous driving
BibRef
Yang, L.[Lei],
Zhang, X.Y.[Xin-Yu],
Yu, J.X.[Jia-Xin],
Li, J.[Jun],
Zhao, T.[Tong],
Wang, L.[Li],
Huang, Y.[Yi],
Zhang, C.[Chuang],
Wang, H.[Hong],
Li, Y.M.[Yi-Ming],
MonoGAE: Roadside Monocular 3D Object Detection With Ground-Aware
Embeddings,
ITS(25), No. 11, November 2024, pp. 17587-17601.
IEEE DOI
2411
Object detection, Cameras, Feature extraction, Training, Robustness,
Geometry, Monocular 3D object detection, roadside perception, autonomous driving
BibRef
Qin, X.C.[Xiao-Chun],
Liu, Y.J.[Yang-Jie],
Yang, D.X.[Dong-Xiao],
Pan, D.[Dangran],
Meng, F.[Fantong],
Cao, Y.F.[Yu-Fei],
Wangari, V.W.[Vicky Wangechi],
Quantitative Characterization of Highway Landscape Space Visual
Perception Based on Deep Learning,
ITS(25), No. 12, December 2024, pp. 21157-21171.
IEEE DOI
2412
Road design to consider landscape in addition to safety.
Road transportation, Visualization, Deep learning, Vehicles,
Analytical models, Indexes, Data models, Roads, Visual perception,
deep learning
BibRef
Xu, J.Q.[Jian-Qiang],
Song, C.Y.[Chun-Ying],
Shi, C.[Chao],
Liu, H.F.[Hua-Feng],
Wang, Q.[Qiong],
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IVC(159), 2025, pp. 105567.
Elsevier DOI
2505
3D object detection, Multi-modal fusion, Uncertainty,
Bird's-Eye-View (BEV) perception
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Misthos, L.M.[Loukas-Moysis],
Krassanakis, V.[Vassilios],
RouteLAND: An Integrated Method and a Geoprocessing Tool for
Characterizing the Dynamic Visual Landscape Along Highways,
IJGI(14), No. 5, 2025, pp. 187.
DOI Link
2505
BibRef
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Perez, M.A.[Michael A.],
Donald, W.N.[Wesley N.],
Bao, Y.[Yin],
A Comparative Study of Deep Semantic Segmentation and UAV-Based
Multispectral Imaging for Enhanced Roadside Vegetation Composition
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2506
BibRef
Zhang, Z.[Zhang],
Sun, C.[Chao],
Wang, B.[Bo],
Guo, B.[Bin],
Wen, D.[Da],
Zhu, T.Y.[Tian-Yi],
Ning, Q.[Qili],
Height3D: A Roadside Visual Framework Based on Height Prediction in
Real 3-D Space,
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IEEE DOI Code:
WWW Link.
2507
Transforms, Accuracy, Feature extraction, Visual perception,
Object detection, Convolution, Visualization, Space vehicles,
roadside perception
BibRef
Ren, Y.N.[Yi-Ning],
Wang, Y.H.[Yin-Hai],
Wu, Z.Z.[Zhi-Zhou],
Antoniou, C.[Constantinos],
Liang, Y.Y.[Yun-Yi],
Road Side Unit Location Optimization Considering Communication
Channel Competition and 6G Technology,
ITS(26), No. 7, July 2025, pp. 9867-9881.
IEEE DOI
2507
Delays, Optimization, Communication channels,
6G mobile communication, Roads, Spread spectrum communication,
progressive hedging algorithm
BibRef
Wang, H.[Huanan],
Zhang, X.Y.[Xin-Yu],
Chen, Z.X.[Zheng-Xian],
Li, J.[Jun],
Liu, H.P.[Hua-Ping],
PDDepth: Pose Decoupled Monocular Depth Estimation for Roadside
Perception System,
CirSysVideo(35), No. 7, July 2025, pp. 6341-6356.
IEEE DOI Code:
WWW Link.
2507
Roadside sensor.
Cameras, Depth measurement, Point cloud compression, Laser radar,
Training, Calibration, Accuracy, Solid modeling, Feature extraction,
roadside perception dataset
BibRef
Yang, L.[Lei],
Zhang, X.Y.[Xin-Yu],
Li, J.[Jun],
Wang, L.[Li],
Zhang, C.[Chuang],
Ju, L.[Li],
Li, Z.W.[Zhi-Wei],
Shen, Y.[Yang],
Lv, C.[Chen],
Wang, H.[Hong],
SGV3D: Toward Scenario Generalization for Vision-Based Roadside 3D
Object Detection,
ITS(26), No. 8, August 2025, pp. 11782-11793.
IEEE DOI Code:
WWW Link.
2508
Detectors, Cameras, Object detection, Accuracy, Pipelines,
Autonomous vehicles, Training, Overfitting, Safety,
autonomous driving
BibRef
Hao, R.Y.[Rui-Yang],
Fan, S.Q.[Si-Qi],
Dai, Y.[Yingru],
Zhang, Z.L.[Zhen-Lin],
Li, C.X.[Chen-Xi],
Wang, Y.T.[Yun-Tian],
Yu, H.[Haibao],
Yang, W.X.[Wen-Xian],
Yuan, J.[Jirui],
Nie, Z.[Zaiqing],
RCooper: A Real-world Large-scale Dataset for Roadside Cooperative
Perception,
CVPR24(22347-22357)
IEEE DOI Code:
WWW Link.
2410
Point cloud compression, Codes, Benchmark testing, Sensor systems,
Sensors, Autonomous vehicles,
dataset and benchmark
BibRef
Taiana, M.[Matteo],
Toso, M.[Matteo],
James, S.[Stuart],
del Bue, A.[Alessio],
PoserNet: Refining Relative Camera Poses Exploiting Object Detections,
ECCV22(XXXIII:247-263).
Springer DOI
2211
BibRef
Ahmad, J.[Javed],
Toso, M.[Matteo],
Taiana, M.[Matteo],
James, S.[Stuart],
del Bue, A.[Alessio],
Multi-view 3D Objects Localization from Street-Level Scenes,
CIAP22(II:89-101).
Springer DOI
2205
BibRef
Waltner, G.[Georg],
Jaschik, M.[Malte],
Rinnhofer, A.[Alfred],
Possegger, H.[Horst],
Bischof, H.[Horst],
An Intelligent Scanning Vehicle for Waste Collection Monitoring,
CIAP22(I:38-50).
Springer DOI
2205
BibRef
Zhu, X.S.[Xiao-Su],
Sheng, H.[Hualian],
Cai, S.[Sijia],
Deng, B.[Bing],
Yang, S.P.[Shao-Peng],
Liang, Q.[Qiao],
Chen, K.[Ken],
Gao, L.[Lianli],
Song, J.K.[Jing-Kuan],
Ye, J.P.[Jie-Ping],
Roscenes: A Large-scale Multi-view 3d Dataset for Roadside Perception,
ECCV24(XLI: 331-347).
Springer DOI
2412
BibRef
Yang, L.[Lei],
Yu, K.C.[Kai-Cheng],
Tang, T.[Tao],
Li, J.[Jun],
Yuan, K.[Kun],
Wang, L.[Li],
Zhang, X.Y.[Xin-Yu],
Chen, P.[Peng],
BEVHeight: A Robust Framework for Vision-based Roadside 3D Object
Detection,
CVPR23(21611-21620)
IEEE DOI
2309
BibRef
Dhiman, V.[Vikas],
Tran, Q.H.[Quoc-Huy],
Corso, J.J.[Jason J.],
Chandraker, M.[Manmohan],
A Continuous Occlusion Model for Road Scene Understanding,
CVPR16(4331-4339)
IEEE DOI
1612
BibRef
Naharudin, N.,
Ahamad, M.S.S.,
Sadullah, A.F.M.,
GIS Data Collection for Pedestrian Facilities and Furniture Using
MAPINR for Android,
GGT16(89-95).
DOI Link
1612
BibRef
Moorfield, B.[Bradley],
Haeusler, R.[Ralf],
Klette, R.[Reinhard],
Bilateral Filtering of 3D Point Clouds for Refined 3D Roadside
Reconstructions,
CAIP15(II:394-402).
Springer DOI
1511
BibRef
Foresti, G.L.,
Pani, B.,
Monitoring motorway infrastructures for detection of dangerous events,
CIAP99(1144-1147).
IEEE DOI
9909
See also On-line trajectory clustering for anomalous events detection.
BibRef
Nicholls, D.C.,
Murray, D.W.,
Applying Visual Processing to GPS Mapping of Trackside Structures,
BMVC98(841-851).
HTML Version.
BibRef
9800
Lanser, S.[Stefan],
Zierl, C.[Christoph],
Munkelt, O.[Olaf],
Radig, B.[Bernd],
MORAL: A vision-based object recognition system for autonomous mobile
systems,
CAIP97(33-41).
Springer DOI
9709
BibRef
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Railroads, Inspection, Obstacles .