15.3.3.7 Obstacle Dectection, Objects on the Road

Li, Z., Filev, D.P., Kolmanovsky, I., Atkins, E., Lu, J.,
A New Clustering Algorithm for Processing GPS-Based Road Anomaly Reports With a Mahalanobis Distance,
ITS(18), No. 7, July 2017, pp. 1980-1988.
IEEE DOI 1706
Algorithm design and analysis, Clustering algorithms, Covariance matrices, Heuristic algorithms, Roads, Vehicles, Evolving clustering algorithm, Mahalanobis distance, Woodbury matrix inversion lemma, road, anomaly, report BibRef

Schaub, A., Baumgartner, D., Burschka, D.,
Reactive Obstacle Avoidance for Highly Maneuverable Vehicles Based on a Two-Stage Optical Flow Clustering,
ITS(18), No. 8, August 2017, pp. 2137-2152.
IEEE DOI 1708
Adaptive optics, Biomedical optical imaging, Cameras, Collision avoidance, Dynamics, Optical imaging, Optical sensors, Collision avoidance, image processing, intelligent vehicles, optical feedback, optimization BibRef

Huang, D.Y.[Deng-Yuan], Chen, C.H.[Chao-Ho], Chen, T.Y.[Tsong-Yi], Hu, W.C.[Wu-Chih], Feng, K.W.[Kai-Wei],
Vehicle detection and inter-vehicle distance estimation using single-lens video camera on urban/suburb roads,
JVCIR(46), No. 1, 2017, pp. 250-259.
Elsevier DOI 1706
Vehicle, detection BibRef

Suhr, J.K., Jung, H.G.,
Rearview Camera-Based Backover Warning System Exploiting a Combination of Pose-Specific Pedestrian Recognitions,
ITS(19), No. 4, April 2018, pp. 1122-1129.
IEEE DOI 1804
Alarm systems, Cameras, Distortion, Feature extraction, Head, Lenses, Optical distortion, Backover warning system, rearview camera BibRef

Al-Mayyahi, A.[Auday], Wang, W.J.[Wei-Ji], Birch, P.[Phil], Hussien, A.[Alaa],
Obstacle detection system based on colour segmentation using monocular vision for an unmanned ground vehicle,
IJCVR(8), No. 3, 2018, pp. 241-266.
DOI Link 1807
BibRef

Rozsa, Z.[Zoltan], Sziranyi, T.[Tamas],
Obstacle Prediction for Automated Guided Vehicles Based on Point Clouds Measured by a Tilted LIDAR Sensor,
ITS(19), No. 8, August 2018, pp. 2708-2720.
IEEE DOI 1808
Laser radar, Robot sensing systems, Shape, Autonomous vehicles, bag of features BibRef

Rozsa, Z.[Zoltan], Sziranyi, T.[Tamas],
Temporal Up-Sampling of LIDAR Measurements Based on a Mono Camera,
CIAP22(II:51-64).
Springer DOI 2205
BibRef

Liu, W.[Wei], Cheng, D.[Dayu], Yin, P.C.[Peng-Cheng], Yang, M.Y.[Meng-Yuan], Li, E.[Erzhu], Xie, M.[Meng], Zhang, L.P.[Lian-Peng],
Small Manhole Cover Detection in Remote Sensing Imagery with Deep Convolutional Neural Networks,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link 1901
BibRef

Su, I.F.[I-Fang], Chen, D.L.[Ding-Li], Lee, C.A.[Chi-Ang], Chung, Y.C.[Yu-Chi],
Finding Visible kNN Objects in the Presence of Obstacles within the User's View Field,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Jia, Y., Cebon, D.,
Measuring the Motion of Vulnerable Road Users Relative to Moving HGVs,
ITS(20), No. 4, April 2019, pp. 1404-1415.
IEEE DOI 1904
Acoustics, Sensor arrays, Motion measurement, Temperature sensors, Ultrasonic variables measurement, Quadratic programming, vulnerable road users BibRef

Burnett, K., Samavi, S., Waslander, S.L., Barfoot, T.D., Schoellig, A.P.,
aUToTrack: A Lightweight Object Detection and Tracking System for the SAE AutoDrive Challenge,
CRV19(209-216)
IEEE DOI 1908
Detectors, Object detection, Laser radar, Benchmark testing, Object Recognition and Detection BibRef

Corcoran, G., Clark, J.,
Traffic Risk Assessment: A Two-Stream Approach Using Dynamic-Attention,
CRV19(166-173)
IEEE DOI 1908
Vehicles, Visualization, Videos, Accidents, Risk management, Hazards, Traffic rick assessment, dynamic-attention, optical flow BibRef

Fraga-Lamas, P.[Paula], Ramos, L.[Lucía], Mondéjar-Guerra, V.[Víctor], Fernández-Caramés, T.M.[Tiago M.],
A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Lin, C.,
Cross Domain Adaptation for on-Road Object Detection Using Multimodal Structure-Consistent Image-to-Image Translation,
ICIP19(3029-3030)
IEEE DOI 1910
generative adversarial network, domain adaptation, image-to-image translation BibRef

Chen, J.Y.[Jun-Ying], Bai, T.Y.[Tong-Yao],
SAANet: Spatial adaptive alignment network for object detection in automatic driving,
IVC(94), 2020, pp. 103873.
Elsevier DOI 2003
Object detection, Fusion-based deep framework, Local orientation encoding, Spatial adaptive alignment, Autonomous driving BibRef

Santana, M.C.S.[Marcos C. S.], Passos Júnior, L.A.[Leandro Aparecido], Moreira, T.P.[Thierry P.], Colombo, D.[Danilo], de Albuquerque, V.H.C.[Victor Hugo C.], Papa, J.P.[João Paulo],
A Novel Siamese-Based Approach for Scene Change Detection With Applications to Obstructed Routes in Hazardous Environments,
IEEE_Int_Sys(35), No. 1, January 2020, pp. 44-53.
IEEE DOI 2004
Decoding, Image segmentation, Semantics, Training data, Neural networks, Intelligent systems, Task analysis, Route Obstruction Detection BibRef

Brambilla, M., Nicoli, M., Soatti, G., Deflorio, F.,
Augmenting Vehicle Localization by Cooperative Sensing of the Driving Environment: Insight on Data Association in Urban Traffic Scenarios,
ITS(21), No. 4, April 2020, pp. 1646-1663.
IEEE DOI 2004
Global navigation satellite system, Sensors, Vehicle-to-everything, Feature extraction, Roads, Standards, controlled arterials BibRef

Leng, J., Liu, Y., Du, D., Zhang, T., Quan, P.,
Robust Obstacle Detection and Recognition for Driver Assistance Systems,
ITS(21), No. 4, April 2020, pp. 1560-1571.
IEEE DOI 2004
Obstacle location, obstacle recognition, U-V disparity map, neural network, road extraction BibRef

Shen, C.[Chao], Zhao, X.M.[Xiang-Mo], Liu, Z.W.[Zhan-Wen], Gao, T.[Tao], Xu, J.[Jiang],
Joint vehicle detection and distance prediction via monocular depth estimation,
IET-ITS(14), No. 7, July 2020, pp. 753-763.
DOI Link 2006
BibRef

Gao, M.[Ming], Jin, L.S.[Li-Sheng], Jiang, Y.Y.[Yu-Ying], Bie, J.[Jing],
Multiple object tracking using a dual-attention network for autonomous driving,
IET-ITS(14), No. 8, August 2020, pp. 842-848.
DOI Link 2007
BibRef

Li, J.[Jing], Shi, X.X.[Xin-Xin], Wang, J.Z.[Jun-Zheng], Yan, M.[Min],
Adaptive road detection method combining lane line and obstacle boundary,
IET-IPR(14), No. 10, August 2020, pp. 2216-2226.
DOI Link 2008
BibRef

Lin, Y.X.[Yong-Xiang], Tan, D.S.[Daniel Stanley], Chen, Y.Y.[Yung-Yao], Huang, C.C.[Ching-Chun], Hua, K.L.[Kai-Lung],
Domain Adaptation With Foreground/Background Cues and Gated Discriminators,
MultMedMag(27), No. 3, July 2020, pp. 44-53.
IEEE DOI 2009
Image segmentation, Semantics, Adaptation models, Logic gates, Automobiles, Training data, Computer science, Autonmous automobiles BibRef

Xue, F., Ming, A., Zhou, Y.,
Tiny Obstacle Discovery by Occlusion-Aware Multilayer Regression,
IP(29), 2020, pp. 9373-9386.
IEEE DOI 1806
Image edge detection, Proposals, Nonhomogeneous media, Roads, Cameras, Training, Obstacle discovery, regression BibRef

Prasad, D.K., Dong, H., Rajan, D., Quek, C.,
Are Object Detection Assessment Criteria Ready for Maritime Computer Vision?,
ITS(21), No. 12, December 2020, pp. 5295-5304.
IEEE DOI 2012
Measurement, Object detection, Sensors, Indexes, Image edge detection, Artificial intelligence, Object detection, performance evaluation BibRef

Chen, L., Zou, Q., Pan, Z., Lai, D., Zhu, L., Hou, Z., Wang, J., Cao, D.,
Surrounding Vehicle Detection Using an FPGA Panoramic Camera and Deep CNNs,
ITS(21), No. 12, December 2020, pp. 5110-5122.
IEEE DOI 2012
Cameras, Videos, Vehicle detection, Lenses, Field programmable gate arrays, Real-time systems, autonomous vehicle BibRef

Hnewa, M., Radha, H.,
Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques,
SPMag(38), No. 1, January 2021, pp. 53-67.
IEEE DOI 2012
Training, Visualization, Object detection, Data models, Safety, Autonomous vehicles, Testing BibRef

Chen, S., Liu, B., Feng, C., Vallespi-Gonzalez, C., Wellington, C.,
3D Point Cloud Processing and Learning for Autonomous Driving: Impacting Map Creation, Localization, and Perception,
SPMag(38), No. 1, January 2021, pp. 68-86.
IEEE DOI 2012
Laser radar, Tools, Sensors, Autonomous vehicles, Surface treatment, Videos BibRef

Carranza-García, M.[Manuel], Torres-Mateo, J.[Jesús], Lara-Benítez, P.[Pedro], García-Gutiérrez, J.[Jorge],
On the Performance of One-Stage and Two-Stage Object Detectors in Autonomous Vehicles Using Camera Data,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Shekar, A.K.[Arvind Kumar], Gou, L.[Liang], Ren, L.[Liu], Wendt, A.[Axel],
Label-Free Robustness Estimation of Object Detection CNNs for Autonomous Driving Applications,
IJCV(129), No. 4, April 2021, pp. 1185-1201.
Springer DOI 2104
BibRef

Li, X.[Xi], Ma, H.M.[Hui-Min], Yi, S.[Sheng], Chen, Y.X.[Yan-Xian], Ma, H.B.[Hong-Bing],
Single annotated pixel based weakly supervised semantic segmentation under driving scenes,
PR(116), 2021, pp. 107979.
Elsevier DOI 2106
Weakly supervised condition, Semantic segmentation, Complex driving scenes, Optimal feature setting BibRef

Lee, H.[Hojoon], Yoon, J.[Jeongsik], Jeong, Y.[Yonghwan], Yi, K.[Kyongsu],
Moving Object Detection and Tracking Based on Interaction of Static Obstacle Map and Geometric Model-Free Approachfor Urban Autonomous Driving,
ITS(22), No. 6, June 2021, pp. 3275-3284.
IEEE DOI 2106
Radar tracking, Laser radar, Real-time systems, Estimation, Target tracking, LiDAR BibRef

Wu, Y.N.[Ya-Nan], Feng, S.H.[Song-He], Huang, X.K.[Xian-Kai], Wu, Z.Z.[Zi-Zhang],
L4Net: An anchor-free generic object detector with attention mechanism for autonomous driving,
IET-CV(15), No. 1, 2021, pp. 36-46.
DOI Link 2106
BibRef

Liu, Y.Z.[Ya-Zhou], Cao, S.[Sen], Lasang, P.[Pongsak], Shen, S.[Shengmei],
Modular Lightweight Network for Road Object Detection Using a Feature Fusion Approach,
SMCS(51), No. 8, August 2021, pp. 4716-4728.
IEEE DOI 2107
Object detection, Feature extraction, Computational modeling, Convolution, Task analysis, Deep learning, Roads, object detection BibRef

Ke, X.[Xiao], Li, J.P.[Jian-Ping],
U-FPNDet: A one-shot traffic object detector based on U-shaped feature pyramid module,
IET-IPR(15), No. 10, 2021, pp. 2146-2156.
DOI Link 2108
Include vehicles and pedestrians. BibRef

Ren, J.[Jia], Zhang, J.[Jing], Cui, Y.[Yani],
Autonomous Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on an Improved Velocity Obstacle Method,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Lu, Q.[Qun], Zhang, D.[Dan], Ye, W.J.[Wen-Jun], Fan, J.Y.[Jing-Yu], Liu, S.[Steven], Su, C.Y.[Chun-Yi],
Targeting Posture Control With Dynamic Obstacle Avoidance of Constrained Uncertain Wheeled Mobile Robots Including Unknown Skidding and Slipping,
SMCS(51), No. 11, November 2021, pp. 6650-6659.
IEEE DOI 2110
Wheels, Mobile robots, Uncertainty, Collision avoidance, Trajectory tracking, Kinematics, Input saturation, wheeled mobile robots (WMRs) BibRef

Cai, Y.F.[Ying-Feng], Dai, L.[Lei], Wang, H.[Hai], Li, Z.X.[Zhi-Xiong],
Multi-Target Pan-Class Intrinsic Relevance Driven Model for Improving Semantic Segmentation in Autonomous Driving,
IP(30), 2021, pp. 9069-9084.
IEEE DOI 2112
Semantics, Feature extraction, Context modeling, Automobiles, Image segmentation, Convolution, Buildings, semantic segmentation BibRef

Zhang, P.P.[Ping-Ping], Liu, W.[Wei], Lei, Y.J.[Yin-Jie], Lu, H.C.[Hu-Chuan],
Semantic Scene Labeling via Deep Nested Level Set,
ITS(22), No. 11, November 2021, pp. 6853-6865.
IEEE DOI 2112
Assisted driving. Level set, Semantics, Labeling, Feature extraction, Deep learning, Image segmentation, Intelligent transportation systems, fully convolutional network BibRef

Yang, K.L.[Kai-Lun], Hu, X.X.[Xin-Xin], Fang, Y.C.[Yi-Cheng], Wang, K.W.[Kai-Wei], Stiefelhagen, R.[Rainer],
Omnisupervised Omnidirectional Semantic Segmentation,
ITS(23), No. 2, February 2022, pp. 1184-1199.
IEEE DOI 2202
Semantics, Image segmentation, Training, Data models, Sensors, Task analysis, Cameras, Intelligent vehicles, scene understanding, omnidirectional images BibRef

Kim, Y.[Youngjun], Hwang, H.Y.[Hyek-Young], Shin, J.[Jitae],
Robust object detection under harsh autonomous-driving environments,
IET-IPR(16), No. 4, 2022, pp. 958-971.
DOI Link 2203
BibRef

Qiao, J.J.[Jian-Jun], Wu, X.[Xiao], He, J.Y.[Jun-Yan], Li, W.[Wei], Peng, Q.[Qiang],
SWNet: A Deep Learning Based Approach for Splashed Water Detection on Road,
ITS(23), No. 4, April 2022, pp. 3012-3025.
IEEE DOI 2204
Roads, Meteorology, Semantics, Deep learning, Accidents, Image segmentation, Water, Splashed water detection, deep learning BibRef

Singh, A.S.P.[Amrik Singh Phuman], Nishihara, O.[Osamu],
Trajectory Tracking and Integrated Chassis Control for Obstacle Avoidance With Minimum Jerk,
ITS(23), No. 5, May 2022, pp. 4625-4641.
IEEE DOI 2205
Tires, Trajectory, Collision avoidance, Force, Friction, Mathematical model, Trajectory tracking, Autonomous vehicle, sliding mode control BibRef

Geisler, S.[Simon], Cunha, C.[Carlos], Satzoda, R.K.[Ravi Kumar],
Better, Faster Small Hazard Detection: Instance-Aware Techniques, Metrics and Benchmarking,
ITS(23), No. 7, July 2022, pp. 9062-9077.
IEEE DOI 2207
Hazards, Semantics, Roads, Image segmentation, Object detection, Measurement, Benchmark testing, Small hazard detection, disparity BibRef

Zhou, W.[Weina], Huang, X.X.[Xin-Xin], Zeng, X.Y.[Xiao-Yang],
Obstacle Detection for Unmanned Surface Vehicles by Fusion Refinement Network,
IEICE(E105-D), No. 8, August 2022, pp. 1393-1400.
WWW Link. 2207
BibRef

Pano, B.[Béatrice], Chevrel, P.[Philippe], Claveau, F.[Fabien], Sentouh, C.[Chouki], Mars, F.[Franck],
Obstacle Avoidance in Highly Automated Cars: Can Progressive Haptic Shared Control Make it Safer and Smoother?,
HMS(52), No. 4, August 2022, pp. 547-556.
IEEE DOI 2208
Vehicles, Torque, Manuals, Wheels, Roads, Haptic interfaces, Autonomous vehicles, Autonomous vehicles, driver behavior, multiobjective ( H_2/H_inf ) control BibRef

Badrloo, S.[Samira], Varshosaz, M.[Masood], Pirasteh, S.[Saied], Li, J.[Jonathan],
Image-Based Obstacle Detection Methods for the Safe Navigation of Unmanned Vehicles: A Review,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Song, P.F.[Peng-Fei], Fan, H.[Hui], Li, J.J.[Jin-Jiang], Hua, F.[Feng],
Attention-Based Multi-Scale Feature Fusion for Free-Space Detection,
IET-ITS(16), No. 9, 2022, pp. 1222-1235.
DOI Link 2208
BibRef

Zhang, H.[Hui], Luo, G.[Guiyang], Li, J.L.[Jing-Lin], Wang, F.Y.[Fei-Yue],
C2FDA: Coarse-to-Fine Domain Adaptation for Traffic Object Detection,
ITS(23), No. 8, August 2022, pp. 12633-12647.
IEEE DOI 2208
Feature extraction, Object detection, Adaptation models, Proposals, Meteorology, Visualization, Detectors, Object detection, intelligent visual perception BibRef

Feng, D.[Di], Wang, Z.N.[Zi-Ning], Zhou, Y.Y.[Yi-Yang], Rosenbaum, L.[Lars], Timm, F.[Fabian], Dietmayer, K.[Klaus], Tomizuka, M.[Masayoshi], Zhan, W.[Wei],
Labels are Not Perfect: Inferring Spatial Uncertainty in Object Detection,
ITS(23), No. 8, August 2022, pp. 9981-9994.
IEEE DOI 2208
Uncertainty, Object detection, Laser radar, Measurement, Probabilistic logic, Detectors, Uncertainty estimation, deep learning BibRef

Liao, J.C.[Jia-Cai], Cao, L.[Libo], Luo, X.L.[Xiao-Le], Sun, X.[Xu], Duan, C.[Cong], Li, J.H.[Jian-Hua], Yuan, F.[Feng],
Road Garbage Segmentation With Deep Supervision and High Fusion Network for Cleaning Vehicles,
ITS(23), No. 8, August 2022, pp. 11190-11204.
IEEE DOI 2208
Roads, Image segmentation, Cleaning, Semantics, Feature extraction, Deep learning, Training, Semantic segmentation, intelligent vehicle BibRef

Bovcon, B.[Borja], Muhovic, J.[Jon], Vranac, D.[Duško], Mozetic, D.[Dean], Perš, J.[Janez], Kristan, M.[Matej],
MODS: A USV-Oriented Object Detection and Obstacle Segmentation Benchmark,
ITS(23), No. 8, August 2022, pp. 13403-13418.
IEEE DOI 2208
Visualization, Object detection, Benchmark testing, Image segmentation, Training, Sea measurements, Surveillance, benchmark BibRef

Song, T.J.[Taek-Jin], Jeong, J.[Jongoh], Kim, J.H.[Jong-Hwan],
End-to-End Real-Time Obstacle Detection Network for Safe Self-Driving via Multi-Task Learning,
ITS(23), No. 9, September 2022, pp. 16318-16329.
IEEE DOI 2209
Semantics, Feature extraction, Roads, Real-time systems, Task analysis, Image segmentation, Point cloud compression, real-time perception BibRef

Shepel, I.[Ilya], Adeshkin, V.[Vasily], Belkin, I.[Ilya], Yudin, D.A.[Dmitry A.],
Occupancy Grid Generation With Dynamic Obstacle Segmentation in Stereo Images,
ITS(23), No. 9, September 2022, pp. 14779-14789.
IEEE DOI 2209
Semantics, Point cloud compression, Laser radar, Cameras, Image segmentation, Sensors, Heuristic algorithms, Occupancy grid, unmanned ground vehicle BibRef

Su, Q.H.[Qing-Hua], Wang, H.D.[Hao-Dong], Xie, M.[Min], Song, Y.[Yue], Ma, S.B.[Shao-Bo], Li, B.X.[Bo-Xiong], Yang, Y.[Ying], Wang, L.[Liyong],
Real-time traffic cone detection for autonomous driving based on YOLOv4,
IET-ITS(16), No. 10, 2022, pp. 1380-1390.
DOI Link 2209
BibRef

Raja, G.[Gunasekaran], Anbalagan, S.[Sudha], Senthilkumar, S.[Senbagapriya], Dev, K.[Kapal], Qureshi, N.M.F.[Nawab Muhammad Faseeh],
SPAS: Smart Pothole-Avoidance Strategy for Autonomous Vehicles,
ITS(23), No. 10, October 2022, pp. 19827-19836.
IEEE DOI 2210
Roads, Speech recognition, Computational modeling, Convolutional neural networks, Autonomous vehicles, speech and gesture recognition BibRef

Li, X.X.[Xiao-Xiao], Xu, Z.H.[Zhi-Hao], Li, S.[Shuai], Su, Z.R.[Ze-Rong], Zhou, X.F.[Xue-Feng],
Simultaneous Obstacle Avoidance and Target Tracking of Multiple Wheeled Mobile Robots With Certified Safety,
Cyber(52), No. 11, November 2022, pp. 11859-11873.
IEEE DOI 2211
Robots, Collision avoidance, Mobile robots, Target tracking, Wheels, Manipulators, Safety, Collision avoidance, motion planning, quadratic programming BibRef

Li, X.X.[Xiao-Xiao], Xu, Z.H.[Zhi-Hao], Su, Z.R.[Ze-Rong], Wang, H.P.[Hong-Peng], Li, S.[Shuai],
Distance- and Velocity-Based Simultaneous Obstacle Avoidance and Target Tracking for Multiple Wheeled Mobile Robots,
ITS(25), No. 2, February 2024, pp. 1736-1748.
IEEE DOI 2402
Robots, Collision avoidance, Mobile robots, Wheels, Kinematics, Task analysis, Safety, Collision avoidance, trajectory tracking, optimization BibRef

Mosbah, R.[Ramzi], Guezouli, L.[Larbi],
Convolutional neural networks for obstacle detection on the road and driving assistance,
IJCVR(12), No. 5, 2022, pp. 573-594.
DOI Link 2211
BibRef

Liu, C.L.[Cheng-Long], Nie, T.[Tong], Du, Y.C.[Yu-Chuan], Cao, J.[Jing], Wu, D.F.[Di-Fei], Li, F.[Feng],
A Response-Type Road Anomaly Detection and Evaluation Method for Steady Driving of Automated Vehicles,
ITS(23), No. 11, November 2022, pp. 21984-21995.
IEEE DOI 2212
Roads, Anomaly detection, Vibrations, Vehicle dynamics, Estimation, Automobiles, Tires, Road anomaly detection, automated vehicles, comfort evaluation BibRef

Ramli, M.F.[Muhammad Faiz], Shamsudin, S.S.[Syariful Syafiq],
Obstacle detection technique to solve poor texture appearance of the obstacle by categorising image's region using cues from expansion of feature points for small UAV,
IJCVR(13), No. 1, 2023, pp. 91-115.
DOI Link 2212
BibRef

Jiang, J.[Jianwu], Li, F.[Fuda], Yang, J.T.[Jun-Tao], Kang, Z.Z.[Zhi-Zhong], Li, J.W.[Jing-Wen],
Construction of indoor obstacle element map based on scene-aware priori obstacle rules,
PandRS(195), 2023, pp. 43-64.
Elsevier DOI 2301
Obstacle element map, Obstacle mobility recognition, Obstacle extraction, Scene recognition, Point cloud semantic segmentation BibRef

Li, F., Wang, H., Akwensi, P.H., Kang, Z.Z.[Zhi-Zhong],
Construction of Obstacle Element Map Based On Indoor Scene Recognition,
Indoor3D19(819-825).
DOI Link 1912
BibRef

Ding, J.C.[Jian-Chuan], Gao, L.P.[Ling-Ping], Liu, W.X.[Wen-Xi], Piao, H.[Haiyin], Pan, J.[Jia], Du, Z.J.[Zhen-Jun], Yang, X.[Xin], Yin, B.C.[Bao-Cai],
Monocular Camera-Based Complex Obstacle Avoidance via Efficient Deep Reinforcement Learning,
CirSysVideo(33), No. 2, February 2023, pp. 756-770.
IEEE DOI 2302
Collision avoidance, Robots, Robot sensing systems, Semantics, Measurement by laser beam, Cameras, Sensors, robot navigation BibRef

Luo, Z.P.[Zhi-Peng], Gao, L.P.[Li-Peng], Xiang, H.D.[Hao-Dong], Li, J.[Jonathan],
Road object detection for HD map: Full-element survey, analysis and perspectives,
PandRS(197), 2023, pp. 122-144.
Elsevier DOI 2303
High-Definition map, Autonomous driving, Road surface information extraction, Road object detection, 3D point clouds BibRef

Chen, Y.L.[Yi-Lun], Huang, S.[Shijia], Liu, S.[Shu], Yu, B.[Bei], Jia, J.Y.[Jia-Ya],
DSGN++: Exploiting Visual-Spatial Relation for Stereo-Based 3D Detectors,
PAMI(45), No. 4, April 2023, pp. 4416-4429.
IEEE DOI 2303
Feature extraction, Detectors, Cameras, Sensors, Costs, Solid modeling, 3D object detection, stereo matching, autonomous driving BibRef

Gao, X.S.[Xiao-Shan], Yan, L.[Liang], Li, Z.J.[Zhi-Jun], Wang, G.[Gang], Chen, I.M.[I-Ming],
Improved Deep Deterministic Policy Gradient for Dynamic Obstacle Avoidance of Mobile Robot,
SMCS(53), No. 6, June 2023, pp. 3675-3682.
IEEE DOI 2305
Mobile robots, Collision avoidance, Heuristic algorithms, Q-learning, Navigation, Fuzzy logic, Force, obstacle avoidance BibRef

Chen, C.[Chen], Yao, G.R.[Guo-Run], Liu, L.[Lei], Pei, Q.Q.[Qing-Qi], Song, H.B.[Hou-Bing], Dustdar, S.[Schahram],
A Cooperative Vehicle-Infrastructure System for Road Hazards Detection With Edge Intelligence,
ITS(24), No. 5, May 2023, pp. 5186-5198.
IEEE DOI 2305
Roads, Image edge detection, Feature extraction, Accidents, Data models, Task analysis, Training, knowledge distillation BibRef

Nguyen, V.D.[Vinh Dinh], Trinh, T.D.[Thong Duc], Tran, H.N.[Hoang Ngoc],
A Robust Triangular Sigmoid Pattern-Based Obstacle Detection Algorithm in Resource-Limited Devices,
ITS(24), No. 6, June 2023, pp. 5936-5945.
IEEE DOI 2306
Feature extraction, Object detection, Roads, Classification algorithms, Lighting, Charge coupled devices, deep learning model BibRef

Wang, Y.T.[Yi-Tian], Lin, J.[Jun], Zhang, L.[Liu], Wang, T.H.[Tian-Hao], Xu, H.[Hao], Qi, Y.[Yuehan], Zhang, G.[Guanyu], Liu, Y.[Yang],
Stable Obstacle Avoidance Strategy for Crawler-Type Intelligent Transportation Vehicle in Non-Structural Environment Based on Attention-Learning,
ITS(24), No. 7, July 2023, pp. 7813-7830.
IEEE DOI 2307
Collision avoidance, Deep learning, Autonomous vehicles, Acoustics, Humanoid robots, Stability criteria, Roads, Attention-LSTM, obstacle avoidance strategy BibRef

Fu, Y.J.[Yong-Jian], Gao, D.[Dingli], Liu, T.[Ting], Zheng, H.[Hang], Hao, D.[Dayang], Pan, Z.J.[Zhi-Jie],
Evolving Into a Transformer: From a Training-Free Retrieval-Based Method for Anomaly Obstacle Segmentation,
IP(32), 2023, pp. 6195-6209.
IEEE DOI 2311
BibRef

Vitale, F.[Francesco], Roncoli, C.[Claudio],
Reference Tracking Optimization With Obstacle Avoidance via Task Prioritization for Automated Driving,
ITS(25), No. 2, February 2024, pp. 1200-1214.
IEEE DOI 2402
Task analysis, Trajectory, Collision avoidance, Behavioral sciences, Safety, Vehicle dynamics, Planning, mixed traffic BibRef

Shi, Y.[Yi], Zhao, S.X.[Shi-Xuan], Wu, J.[Jiang], Wu, Z.B.[Zhang-Bi], Yan, H.M.[Hong-Mei],
Fixated Object Detection Based on Saliency Prior in Traffic Scenes,
CirSysVideo(34), No. 3, March 2024, pp. 1413-1426.
IEEE DOI Code:
WWW Link. 2403
Object detection, Visualization, Task analysis, Computational modeling, Predictive models, Safety, Vehicles, deep learning BibRef

Kuang, J.J.[Jian-Jie], Tan, G.F.[Gang-Feng], Guo, X.X.[Xue-Xun], Pei, X.F.[Xiao-Fei], Peng, D.Z.[Deng-Zhi],
Research of obstacle vehicles avoidance for automated heavy vehicle platoon by switching the formation,
IET-ITS(18), No. 4, 2024, pp. 630-644.
DOI Link 2404
automated driving and intelligent vehicles, collision avoidance, decision making, path planning, velocity control BibRef

Zhang, X.Z.[Xi-Zheng], Cao, X.[Xu], Zhang, H.[Hui], Shen, Y.P.[Yong-Peng], Yuan, X.F.[Xiao-Fang], Cui, Z.J.[Zi-Jian], Lu, Z.Y.[Zhang-Yu],
An Intelligent Obstacle Detection for Autonomous Mining Transportation With Electric Locomotive via Cellular Vehicle-to-Everything and Vehicular Edge Computing,
ITS(25), No. 3, March 2024, pp. 3177-3190.
IEEE DOI 2405
Feature extraction, 6G mobile communication, Transportation, Image edge detection, Edge computing, Detection algorithms, attention mechanism BibRef

Sun, B.Y.[Bang-Yong], Ma, M.[Ming], Yuan, N.Z.[Nian-Zeng], Li, J.H.[Jun-Huai], Yu, T.[Tao],
Detecting the Background-Similar Objects in Complex Transportation Scenes,
ITS(25), No. 3, March 2024, pp. 2920-2932.
IEEE DOI 2405
Feature extraction, Task analysis, Semantics, Roads, Object detection, Meteorology, Transportation, guide-learning BibRef

Ding, M.[Meng], Guan, S.[Song], Liu, H.[Hao], Yu, K.[Kuaikuai],
TIR-YOLO-ADAS: A thermal infrared object detection framework for advanced driver assistance systems,
IET-ITS(18), No. 5, 2024, pp. 822-834.
DOI Link 2405
advanced driver assistance systems, infrared detectors, object detection BibRef

Zhu, Y.[Yuan], Xu, R.D.[Rui-Dong], Tao, C.[Chongben], An, H.[Hao], Wang, H.[Huaide], Sun, Z.P.[Zhi-Peng], Lu, K.[Ke],
DS-Trans: A 3D Object Detection Method Based on a Deformable Spatiotemporal Transformer for Autonomous Vehicles,
RS(16), No. 9, 2024, pp. 1621.
DOI Link 2405
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Du, B.[Bin], Xie, W.[Wei], Zhang, W.D.[Wei-Dong], Chen, H.T.[Hong-Tian],
A Target Tracking Guidance for Unmanned Surface Vehicles in the Presence of Obstacles,
ITS(25), No. 5, May 2024, pp. 4102-4115.
IEEE DOI Code:
WWW Link. 2405
Target tracking, Navigation, Collision avoidance, Vehicle dynamics, Rivers, Reinforcement learning, Marine vehicles, obstacle avoidance BibRef

Liu, Y.Z.[Ya-Zhou], Wei, X.Y.[Xiang-Yu], Lasang, P.[Pongsak], Pranata, S.[Sugiri], Subramanian, K.[Karthikk], Seow, H.[Hocktong],
Ensemble Uncertainty Guided Road Scene Anomaly Detection: A Simple Meta-Learning Approach,
ITS(25), No. 9, September 2024, pp. 10754-10765.
IEEE DOI Code:
WWW Link. 2409
Uncertainty, Roads, Anomaly detection, Training data, Data models, Training, Task analysis, Anomaly detection, semantic segmentation, meta learning BibRef

Fan, J.[Jiayu], Murgovski, N.[Nikolce], Liang, J.[Jun], Elawad, A.[Amal],
Exact Obstacle Avoidance for Autonomous Vehicles in Polygonal Domains,
SMCS(54), No. 10, October 2024, pp. 5964-5976.
IEEE DOI 2410
Collision avoidance, Autonomous vehicles, Trajectory planning, Planning, Shape, Trajectory, Vectors, Autonomous vehicles, nonconvex vehicles and obstacles BibRef

Zeng, S.[Shuai], Zheng, W.Z.[Wen-Zhao], Lu, J.W.[Ji-Wen], Yan, H.B.[Hai-Bin],
Hardness-Aware Scene Synthesis for Semi-Supervised 3D Object Detection,
MultMed(26), 2024, pp. 9644-9656.
IEEE DOI 2410
Object detection, Point cloud compression, Training, Semisupervised learning, Data models, Predictive models, autonomous driving BibRef

Gratzer, A.L.[Alexander L.], Broger, M.M.[Maximilian M.], Schirrer, A.[Alexander], Jakubek, S.[Stefan],
Two-Layer MPC Architecture for Efficient Mixed-Integer-Informed Obstacle Avoidance in Real-Time,
ITS(25), No. 10, October 2024, pp. 13767-13784.
IEEE DOI 2410
Collision avoidance, Real-time systems, Predictive models, Computer architecture, Computational modeling, Vehicle dynamics, single-track model BibRef

Zhang, H.C.[Han-Cheng], Hu, Y.Y.[Yuan-Yuan], Qian, Z.D.[Zhen-Dong], Sha, J.[Jirui], Xie, M.[Min], Wan, Y.Y.[Yu-Yang], Liu, P.F.[Peng-Fei],
Enhancing Rare Object Detection on Roadways Through Conditional Diffusion Models for Data Augmentation,
ITS(25), No. 11, November 2024, pp. 19018-19029.
IEEE DOI 2411
Diffusion models, Training, Object detection, Accuracy, Roads, Noise measurement, Gaussian noise, Traffic scene perception, data augmentation BibRef

Chen, H.[Hao], Min, B.W.[Byung-Won], Zhang, H.[Haifei],
A study on a target detection model for autonomous driving tasks,
IET-IPR(18), No. 12, 2024, pp. 3447-3459.
DOI Link 2411
image classification, image processing, learning (artificial intelligence) BibRef

Song, Z.[Ziying], Liu, L.[Lin], Jia, F.[Feiyang], Luo, Y.[Yadan], Jia, C.Y.[Cai-Yan], Zhang, G.X.[Guo-Xin], Yang, L.[Lei], Wang, L.[Li],
Robustness-Aware 3D Object Detection in Autonomous Driving: A Review and Outlook,
ITS(25), No. 11, November 2024, pp. 15407-15436.
IEEE DOI 2411
Robustness, Object detection, Autonomous vehicles, Accuracy, Sensors, Noise, 3D object detection, perception, robustness, autonomous driving BibRef

Lin, J.P.[Jin-Peng], Liang, Z.H.[Zhi-Hao], Deng, S.[Shengheng], Cai, L.[Lile], Jiang, T.[Tao], Li, T.R.[Tian-Rui], Jia, K.[Kui], Xu, X.[Xun],
Exploring Diversity-Based Active Learning for 3D Object Detection in Autonomous Driving,
ITS(25), No. 11, November 2024, pp. 15454-15466.
IEEE DOI 2411
Object detection, Costs, Annotations, Detectors, Uncertainty, Diversity reception, Feature extraction, Autonomous vehicles, autonomous driving BibRef

Shi, Y.N.[Yi-Ning], Jiang, K.[Kun], Wang, K.[Ke], Li, J.[Jiusi], Wang, Y.L.[Yun-Long], Yang, M.M.[Meng-Meng], Yang, D.[Diange],
StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation,
CVPR24(14833-14842)
IEEE DOI 2410
Training, Interpolation, Recurrent neural networks, Ordinary differential equations, Sensor fusion, Streaming perception BibRef

Tang, P.[Pin], Wang, Z.D.[Zhong-Dao], Wang, G.Q.[Guo-Qing], Zheng, J.[Jilai], Ren, X.X.[Xiang-Xuan], Feng, B.[Bailan], Ma, C.[Chao],
SparseOcc: Rethinking Sparse Latent Representation for Vision-Based Semantic Occupancy Prediction,
CVPR24(15035-15044)
IEEE DOI 2410
Interpolation, Technological innovation, Solid modeling, Sparse approximation, Scalability, Semantics, Occupancy Prediction, Autonomous Driving BibRef

Huang, K.C.[Kuan-Chih], Lyu, W.J.[Wei-Jie], Yang, M.H.[Ming-Hsuan], Tsai, Y.H.[Yi-Hsuan],
PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection,
CVPR24(14938-14947)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Representation learning, Runtime, Memory management, Object detection, Detectors, Autonomous Driving BibRef

Xia, Y.[Yan], Shi, L.[Letian], Ding, Z.[Zifeng], Henriques, J.F.[João F.], Cremers, D.[Daniel],
Text2Loc: 3D Point Cloud Localization from Natural Language,
CVPR24(14958-14967)
IEEE DOI Code:
WWW Link. 2410
Location awareness, Point cloud compression, Visualization, Accuracy, Semantics, Pipelines, 3D localization, point cloud, text, autonomous driving BibRef

Shoeb, Y., Chan, R., Schwalbe, G., Nowzad, A., Güney, F., Gottschalk, H.,
Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes,
WACV24(7381-7391)
IEEE DOI 2404
Image segmentation, Roads, Training data, Streaming media, Safety, Recording, Task analysis, Applications, Autonomous Driving, Vision + language and/or other modalities BibRef

Tong, W.W.[Wen-Wen], Sima, C.[Chonghao], Wang, T.[Tai], Chen, L.[Li], Wu, S.[Silei], Deng, H.M.[Han-Ming], Gu, Y.[Yi], Lu, L.W.[Le-Wei], Luo, P.[Ping], Lin, D.[Dahua], Li, H.Y.[Hong-Yang],
Scene as Occupancy,
ICCV23(8372-8381)
IEEE DOI 2401
BibRef

Wei, Y.[Yi], Zhao, L.Q.[Lin-Qing], Zheng, W.Z.[Wen-Zhao], Zhu, Z.[Zheng], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving,
ICCV23(21672-21683)
IEEE DOI Code:
WWW Link. 2401
BibRef

Agro, B.[Ben], Sykora, Q.[Quinlan], Casas, S.[Sergio], Urtasun, R.[Raquel],
Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving,
CVPR23(1379-1388)
IEEE DOI 2309
BibRef

Choe, T.E.[Tae Eun], Wu, J.[Jane], Lin, X.L.[Xiao-Lin], Kwon, K.[Karen], Park, M.W.[Min-Woo],
HazardNet: Road Debris Detection by Augmentation of Synthetic Models,
WAD23(161-171)
IEEE DOI 2309
BibRef

Lambert, R.[Reeve], Li, J.W.[Jian-Wen], Chavez-Galaviz, J.[Jalil], Mahmoudian, N.[Nina],
A Survey on the Deployability of Semantic Segmentation Networks for Fluvial Navigation,
Maritime23(255-264)
IEEE DOI 2302
Training, Embedded systems, Navigation, Semantic segmentation, Semantics, Neural networks, Training data BibRef

Tian, Y.[Yu], Liu, Y.Y.[Yu-Yuan], Pang, G.S.[Guan-Song], Liu, F.[Fengbei], Chen, Y.H.[Yuan-Hong], Carneiro, G.[Gustavo],
Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes,
ECCV22(XXIX:246-263).
Springer DOI 2211
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Li, K.[Kaican], Chen, K.[Kai], Wang, H.Y.[Hao-Yu], Hong, L.Q.[Lan-Qing], Ye, C.Q.[Chao-Qiang], Han, J.H.[Jian-Hua], Chen, Y.[Yukuai], Zhang, W.[Wei], Xu, C.J.[Chun-Jing], Yeung, D.Y.[Dit-Yan], Liang, X.D.[Xiao-Dan], Li, Z.G.[Zhen-Guo], Xu, H.[Hang],
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving,
ECCV22(XXXVIII:406-423).
Springer DOI 2211
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Luo, C.X.[Chen-Xu], Yang, X.D.[Xiao-Dong], Yuille, A.L.[Alan L.],
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving,
ICCV21(10468-10477)
IEEE DOI 2203
Point cloud compression, Solid modeling, Pediatrics, Laser radar, Tracking, Motion estimation, Motion and tracking, BibRef

Jung, S.[Sanghun], Lee, J.[Jungsoo], Gwak, D.[Daehoon], Choi, S.[Sungha], Choo, J.[Jaegul],
Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation,
ICCV21(15405-15414)
IEEE DOI 2203
Training, Image segmentation, Visualization, Smoothing methods, Roads, Semantics, Vision for robotics and autonomous vehicles, grouping and shape BibRef

Žust, L.[Lojze], Kristan, M.[Matej],
Learning Maritime Obstacle Detection from Weak Annotations by Scaffolding,
WACV22(1888-1897)
IEEE DOI 2202
Training, Costs, Annotations, Image edge detection, Sea measurements, Labeling, Vision for Robotics BibRef

Robinet, F.[François], Parera, C.[Claudia], Hundt, C.[Christian], Frank, R.[Raphaël],
Weakly-Supervised Free Space Estimation through Stochastic Co-Teaching,
Hazards22(618-627)
IEEE DOI 2202
Training, Image segmentation, Adaptation models, Annotations, Stochastic processes, Estimation, Training data BibRef

Liu, P.[Pei], Yang, G.R.[Guo-Run], Li, P.X.[Pei-Xuan], Wang, Z.[Zhe], Shi, J.P.[Jian-Ping], Deng, Z.D.[Zhi-Dong], Qiao, Y.[Yu],
MP-Mono: Monocular 3D Detection Using Multiple Priors for Autonomous Driving,
3DV21(535-544)
IEEE DOI 2201
Geometry, Shape, Clustering algorithms, Object detection, Inference algorithms, Proposals BibRef

Karakostas, I.[Iason], Mygdalis, V.[Vasileios], Pitas, I.[Ioannis],
Adversarial Optimization Scheme for Online Tracking Model Adaptation In Autonomous Systems,
ICIP21(3358-3362)
IEEE DOI 2201
Training, Adaptation models, Visualization, Target tracking, Embedded systems, Computational modeling, Computer architecture, autonomous systems BibRef

Kishore, A.[Aman], Choe, T.E.[Tae Eun], Kwon, J.[Junghyun], Park, M.W.[Min-Woo], Hao, P.F.[Peng-Fei], Mittel, A.[Akshita],
Synthetic Data Generation using Imitation Training,
AVVision21(3071-3079)
IEEE DOI 2112
Training, Measurement, Deep learning, Machine learning algorithms, Estimation, Object detection BibRef

Besnier, V.[Victor], Picard, D.[David], Briot, A.[Alexandre],
Learning Uncertainty for Safety-Oriented Semantic Segmentation in Autonomous Driving,
ICIP21(3353-3357)
IEEE DOI 2201
Training, Uncertainty, Measurement uncertainty, Semantics, Estimation, Training data, Observers, Uncertainty, Segmentation, Autonomous Driving BibRef

Duong, L.H.[Le Hoang], Trung, H.T.[Huynh Thanh], Tam, P.M.[Pham Minh], Ko, G.[Gwangzeen], Moon, J.I.[Jung Ick], Jo, J.[Jun], Hung, N.Q.V.[Nguyen Quoc Viet],
ODAR: A Lightweight Object Detection Framework for Autonomous Driving Robots,
DICTA21(01-08)
IEEE DOI 2201
Deep learning, Wireless communication, Computational modeling, Object detection, Detectors, Feature extraction, Real-time systems, deep neural network BibRef

Sagar, A.[Abhinav], Soundrapandiyan, R.[RajKumar],
Semantic Segmentation With Multi Scale Spatial Attention For Self Driving Cars,
VSPW21(2650-2656)
IEEE DOI 2112
Measurement, Training, Image segmentation, Semantics, Neural networks BibRef

Agarwal, A.[Ashutosh], Majee, A.[Anay], Subramanian, A.[Anbumani], Arora, C.[Chetan],
Attention Guided Cosine Margin to Overcome Class-Imbalance in Few-Shot Road Object Detection,
Novelty22(221-230)
IEEE DOI 2202
Measurement, Head, Roads, Detectors, Object detection, Benchmark testing BibRef

Tambwekar, A.[Anuj], Agrawal, K.[Kshitij], Majee, A.[Anay], Subramanian, A.[Anbumani],
Few-Shot Batch Incremental Road Object Detection via Detector Fusion,
AVVision21(3063-3070)
IEEE DOI 2112
Deep learning, Roads, Object detection, Detectors, Robustness BibRef

Reuse, M.[Matthias], Simon, M.[Martin], Sick, B.[Bernhard],
About the Ambiguity of Data Augmentation for 3D Object Detection in Autonomous Driving,
ERCVAD21(979-987)
IEEE DOI 2112
Training, Manifolds, Detectors, Object detection BibRef

Plebe, A.[Alice], Kooij, J.F.P.[Julian F. P.], Papini, G.P.R.[Gastone Pietro Rosati], da Lio, M.[Mauro],
Occupancy Grid Mapping with Cognitive Plausibility for Autonomous Driving Applications,
AVVision21(2934-2941)
IEEE DOI 2112
Visualization, Navigation, Information filters, Cognition, Vehicle dynamics BibRef

Fugošic, K.[Kristijan], Šaric, J.[Josip], Šegvic, S.[Siniša],
Multimodal Semantic Forecasting Based on Conditional Generation of Future Features,
GCPR20(474-487).
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Rahman, Q.M.[Quazi Marufur], Sünderhauf, N.[Niko], Dayoub, F.[Feras],
Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment,
WACVW21(152-160) Autonomous Vehicle Vision
IEEE DOI 2105
Measurement, Deep learning, Object detection, Detectors, Feature extraction BibRef

Wang, W.[Wei], Zhou, S.[Shibo], Li, J.X.[Jing-Xi], Li, X.H.[Xiao-Hua], Yuan, J.S.[Jun-Song], Jin, Z.P.[Zhan-Peng],
Temporal Pulses Driven Spiking Neural Network for Time and Power Efficient Object Recognition in Autonomous Driving,
ICPR21(6359-6366)
IEEE DOI 2105
Laser radar, Power demand, Computational modeling, Neural networks, Vision sensors, Real-time systems, Object recognition BibRef

Tian, K.[Kun], Zhou, T.[Tong], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
Forground-Guided Vehicle Perception Framework,
ICPR21(8015-8020)
IEEE DOI 2105
Training, Deep learning, Visualization, Vehicle detection, Pattern recognition, Task analysis, attention BibRef

Metzger, K.A.[Kai A.], Mortimer, P.[Peter], Wuensche, H.J.[Hans-Joachim],
A Fine-Grained Dataset and its Efficient Semantic Segmentation for Unstructured Driving Scenarios,
ICPR21(7892-7899)
IEEE DOI 2105
Semantics, Vegetation mapping, Lighting, Autonomous vehicles, Meteorology, vegetation dataset, efficient BibRef

Ohgushi, T.[Toshiaki], Horiguchi, K.[Kenji], Yamanaka, M.[Masao],
Road Obstacle Detection Method Based on an Autoencoder with Semantic Segmentation,
ACCV20(VI:223-238).
Springer DOI 2103
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Li, P.X.[Pei-Xuan], Zhao, H.[Huaici], Liu, P.F.[Peng-Fei], Cao, F.[Feidao],
RTM3D: Real-time Monocular 3d Detection from Object Keypoints for Autonomous Driving,
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Wang, J.[Jun], Lan, S.Y.[Shi-Yi], Gao, M.F.[Ming-Fei], Davis, L.S.[Larry S.],
Infofocus: 3d Object Detection for Autonomous Driving with Dynamic Information Modeling,
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Unsupervised Temporal Consistency Metric for Video Segmentation in Highly-Automated Driving,
SAIAD20(1369-1378)
IEEE DOI 2008
Semantics, Measurement, Image segmentation, Optical imaging, Video sequences, Adaptive optics, Nonlinear optics BibRef

Walsh, S.[Sean], Ku, J.[Jason], Pon, A.D.[Alex D.], Waslander, S.L.[Steven L.],
Leveraging Temporal Data for Automatic Labelling of Static Vehicles,
CRV20(134-141)
IEEE DOI 2006
The vehicle maps to the same location each frame. labelling, object detection, dataset, 3D BibRef

Chen, N.F.Y.,
Pseudo-Labels for Supervised Learning on Dynamic Vision Sensor Data, Applied to Object Detection Under Ego-Motion,
ECVW18(757-75709)
IEEE DOI 1812
Vision sensors, Cameras, Vehicle dynamics, Object detection, Voltage control, Supervised learning, Automobiles BibRef

Khodabandeh, M.[Mehran], Vahdat, A.[Arash], Ranjbar, M.[Mani], Macready, W.[William],
A Robust Learning Approach to Domain Adaptive Object Detection,
ICCV19(480-490)
IEEE DOI 2004
learning (artificial intelligence), object detection, domain shift, unconstrained road environments, Computational modeling BibRef

Choi, H.M.[Hee Min], Kang, H.[Hyoa], Hyun, Y.[Yoonsuk],
Multi-View Reprojection Architecture for Orientation Estimation,
ADW19(2357-2366)
IEEE DOI 2004
geometry, image motion analysis, image reconstruction, object detection, pose estimation, regression analysis, MVRA BibRef

Ma, X., Wang, Z., Li, H., Zhang, P., Ouyang, W., Fan, X.,
Accurate Monocular 3D Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving,
ICCV19(6850-6859)
IEEE DOI 2004
driver information systems, feature extraction, image colour analysis, image fusion, image reconstruction, Transforms BibRef

Blum, H., Sarlin, P., Nieto, J., Siegwart, R., Cadena, C.,
Fishyscapes: A Benchmark for Safe Semantic Segmentation in Autonomous Driving,
ADW19(2403-2412)
IEEE DOI 2004
Bayes methods, image segmentation, learning (artificial intelligence), mobile robots, deep learning for robotics BibRef

Hua, M., Nan, Y., Lian, S.,
Small Obstacle Avoidance Based on RGB-D Semantic Segmentation,
CVRSUAD19(886-894)
IEEE DOI 2004
cameras, collision avoidance, image capture, image colour analysis, image segmentation, image sensors, image sequences, motion blur BibRef

Dahal, A., Hossen, J., Sumanth, C., Sistu, G., Malhan, K., Amasha, M., Yogamani, S.,
DeepTrailerAssist: Deep Learning Based Trailer Detection, Tracking and Articulation Angle Estimation on Automotive Rear-View Camera,
ADW19(2339-2346)
IEEE DOI 2004
cameras, driver information systems, embedded systems, learning (artificial intelligence), neural nets, Deep Learning BibRef

Orsic, M.[Marin], Kreso, I.[Ivan], Bevandic, P.[Petra], Segvic, S.[Sinisa],
In Defense of Pre-Trained ImageNet Architectures for Real-Time Semantic Segmentation of Road-Driving Images,
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Yang, J., Kang, Z.,
A Gradient-region Constrained Level Set Method for Autonomous Rock Detection From Mars Rover Image,
PRSM19(1479-1485).
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Wang, Y., Peng, M., Di, K., Wan, W., Liu, Z., Yue, Z., Xing, Y., Mao, X., Teng, B.,
Vision Based Obstacle Detection Using Rover Stereo Images,
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Hashimoto, S., Mori, K.,
System Construction for Both Lunar Obstacle Detection and Annotation Support Based on Neurons' Decision Validity,
ICIP19(3447-3451)
IEEE DOI 1910
Deep learning, lunar crater, annotation BibRef

Liu, R., Luo, F., Yuan, Z.,
Beyond Bounding Box: Fine-Grained Vehicle Detection via Single Stage Detector with Hierarchical output,
ICIP19(3950-3954)
IEEE DOI 1910
vehicle detection, beyond bounding box, autonomous driving, deep learning BibRef

Kiran, B.R.[B. Ravi], Roldão, L.[Luis], Irastorza, B.[Beñat], Verastegui, R.[Renzo], Süss, S.[Sebastian], Yogamani, S.[Senthil], Talpaert, V.[Victor], Lepoutre, A.[Alexandre], Trehard, G.[Guillaume],
Real-Time Dynamic Object Detection for Autonomous Driving Using Prior 3D-Maps,
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Hsu, Y., Zhong, K., Perng, J., Yin, T., Chen, C.,
Developing an On-Road Obstacle Detection System Using Monovision,
IVCNZ18(1-9)
IEEE DOI 1902
Feature extraction, Classification algorithms, Automobiles, Motorcycles, Support vector machines, Cameras, Object recognition, object recognition BibRef

Saleem, N.H., Griffin, A., Klette, R.,
Monocular Stixels: A LIDAR-guided Approach,
IVCNZ18(1-6)
IEEE DOI 1902
Laser radar, Cameras, Roads, Estimation, Sensors, Interpolation BibRef

Garcia, A.S., Figueroa, H.R., Hernandez, A.M., Ramirez, E.R., Uribe, D.O.,
Finding learned obstacles to avoid collisions in autonomous robotic navigation,
IVCNZ17(1-5)
IEEE DOI 1902
collision avoidance, image colour analysis, image segmentation, image sequences, learning (artificial intelligence), Apparent size BibRef

Li, P.L.[Pei-Liang], Qin, T.[Tong], Shen, S.J.[Shao-Jie],
Stereo Vision-Based Semantic 3D Object and Ego-Motion Tracking for Autonomous Driving,
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Patra, S., Maheshwari, P., Yadav, S., Banerjee, S., Arora, C.,
A Joint 3D-2D Based Method for Free Space Detection on Roads,
WACV18(643-652)
IEEE DOI 1806
SLAM (robots), cameras, feature extraction, image classification, image representation, image segmentation, image sequences, BibRef

Anisimov, D., Khanova, T.,
Towards lightweight convolutional neural networks for object detection,
AVSS17(1-8)
IEEE DOI 1806
feature extraction, inference mechanisms, object detection, road vehicles, self-organising feature maps, Real-time systems BibRef

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Probabilistic Obstacle Partitioning of Monocular Video for Autonomous Vehicles,
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Fast Vehicle Detector for Autonomous Driving,
CVRoads17(222-229)
IEEE DOI 1802
Detectors, Feature extraction, Object detection, Proposals, Real-time systems, Training, Vehicle detection BibRef

Garnett, N., Silberstein, S., Oron, S., Fetaya, E., Verner, U., Ayash, A., Goldner, V., Cohen, R., Horn, K., Levi, D.,
Real-Time Category-Based and General Obstacle Detection for Autonomous Driving,
CVRoads17(198-205)
IEEE DOI 1802
Laser radar, Neurons, Object detection, Pose estimation, Training BibRef

Kostavelis, I.[Ioannis], Kargakos, A.[Andreas], Giakoumis, D.[Dimitrios], Tzovaras, D.[Dimitrios],
Robot's Workspace Enhancement with Dynamic Human Presence for Socially-Aware Navigation,
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Embedded Robust Visual Obstacle Detection on Autonomous Lawn Mowers,
ECVW17(361-369)
IEEE DOI 1709
Cameras, Collision avoidance, Image color analysis, Image segmentation, Robots, Robustness, Sun BibRef

Gaisser, F., Jonker, P.P.,
Road user detection with convolutional neural networks: An application to the autonomous shuttle WEpod,
MVA17(101-104)
DOI Link 1708
Cameras, Radar detection, Roads, Sensors, Vehicle dynamics, Visualization BibRef

El Mikaty, M., Stathaki, T.,
Detection of cars in complex urban areas,
MVA17(105-108)
DOI Link 1708
Automobiles, Covariance matrices, Eigenvalues and eigenfunctions, Feature extraction, Histograms, Image, color, analysis BibRef

Carrillo, D.A.P., Sutherland, A.,
Fast Obstacle Detection Using Sparse Edge-Based Disparity Maps,
3DV16(66-72)
IEEE DOI 1701
image segmentation BibRef

Saleh, K., Hossny, M., Nahavandi, S.,
Kangaroo Vehicle Collision Detection Using Deep Semantic Segmentation Convolutional Neural Network,
DICTA16(1-7)
IEEE DOI 1701
Cameras BibRef