Chen, B.,
Gong, C.,
Yang, J.,
Importance-Aware Semantic Segmentation for Autonomous Vehicles,
ITS(20), No. 1, January 2019, pp. 137-148.
IEEE DOI
1901
Image segmentation, Autonomous vehicles, Roads, Neural networks,
Feature extraction, Semantics, Reliability, Semantic segmentation,
autonomous driving
BibRef
Zhang, Y.[Yang],
David, P.[Philip],
Foroosh, H.[Hassan],
Gong, B.Q.[Bo-Qing],
A Curriculum Domain Adaptation Approach to the Semantic Segmentation
of Urban Scenes,
PAMI(42), No. 8, August 2020, pp. 1823-1841.
IEEE DOI
2007
BibRef
Earlier: A1, A2, A4, Only:
Curriculum Domain Adaptation for Semantic Segmentation of Urban
Scenes,
ICCV17(2039-2049)
IEEE DOI
1802
Semantics, Image segmentation, Task analysis, Adaptation models,
Neural networks, Training, Buildings, Domain adaptation,
self-driving.
computer graphics, convolution, image classification,
learning (artificial intelligence).
BibRef
Wang, Y.D.[Yi-Dong],
Mo, L.[Lisha],
Ma, H.M.[Hui-Min],
Yuan, J.[Jian],
OccGAN: Semantic image augmentation for driving scenes,
PRL(136), 2020, pp. 257-263.
Elsevier DOI
2008
Occlusion, GAN, Semantic, Augmentation, Cityscapes
BibRef
Yang, K.,
Hu, X.,
Stiefelhagen, R.,
Is Context-Aware CNN Ready for the Surroundings? Panoramic Semantic
Segmentation in the Wild,
IP(30), 2021, pp. 1866-1881.
IEEE DOI
2101
Image segmentation, Semantics, Training, Cameras, Task analysis,
Benchmark testing, Context modeling, Scene understanding,
autonomous driving
BibRef
Liu, X.F.[Xiao-Feng],
Lu, Y.H.[Yun-Hong],
Liu, X.C.[Xiong-Chang],
Bai, S.[Song],
Li, S.[Site],
You, J.[Jane],
Wasserstein Loss With Alternative Reinforcement Learning for
Severity-Aware Semantic Segmentation,
ITS(23), No. 1, January 2022, pp. 587-596.
IEEE DOI
2201
Automobiles, Measurement, Roads, Semantics, Optimization, Training,
Histograms, Semantic segmentation, autonomous driving,
actor-critic
BibRef
Liu, X.F.[Xiao-Feng],
Ji, W.X.[Wen-Xuan],
You, J.[Jane],
El Fakhri, G.[Georges],
Woo, J.H.[Jong-Hye],
Severity-Aware Semantic Segmentation With Reinforced Wasserstein
Training,
CVPR20(12563-12572)
IEEE DOI
2008
Semantics, Autonomous vehicles, Measurement, Automobiles, Histograms,
Training, Roads
BibRef
Xie, B.Q.[Bang-Quan],
Yang, Z.M.[Zong-Ming],
Yang, L.[Liang],
Luo, R.[Ruifa],
Wei, A.[Ailin],
Weng, X.X.[Xiao-Xiong],
Li, B.[Bing],
Multi-Scale Fusion With Matching Attention Model: A Novel Decoding
Network Cooperated With NAS for Real-Time Semantic Segmentation,
ITS(23), No. 8, August 2022, pp. 12622-12632.
IEEE DOI
2208
Feature extraction, Semantics, Real-time systems,
Image segmentation, Encoding, Decoding,
autonomous driving
BibRef
Jin, Z.[Zhenyi],
Dou, F.[Furong],
Feng, Z.L.[Zi-Liang],
Zhang, C.F.[Cheng-Fang],
BSNet: A bilateral real-time semantic segmentation network based on
multi-scale receptive fields,
JVCIR(102), 2024, pp. 104188.
Elsevier DOI
2407
Road scenes, Real-time semantic segmentation,
Multi-scale receptive fields Bilateral network, Short-term dense concatenate
BibRef
Wang, X.W.[Xiao-Wei],
Jiang, P.W.[Pei-Wen],
Li, Y.[Yang],
Hu, M.J.[Man-Jiang],
Gao, M.[Ming],
Cao, D.[Dongpu],
Ding, R.J.[Rong-Jun],
Progressive Critical Region Transfer for Cross-Domain Visual Object
Detection,
ITS(25), No. 8, August 2024, pp. 9427-9441.
IEEE DOI
2408
Detectors, Semantics, Visualization, Training, Object detection,
Feature extraction, Prototypes, Autonomous driving,
progressive critical region transfer
BibRef
Cai, M.J.[Min-Jie],
Kezierbieke, J.[Jianaresi],
Zhong, X.H.[Xiong-Hu],
Chen, H.[Hao],
Uncertainty-Aware and Class-Balanced Domain Adaptation for Object
Detection in Driving Scenes,
ITS(25), No. 11, November 2024, pp. 15977-15990.
IEEE DOI
2411
Uncertainty, Object detection, Adaptation models, Estimation,
Bayes methods, Detectors, Feature extraction, Object detection,
uncertainty estimation
BibRef
Guan, L.[Licong],
Yuan, X.[Xue],
Dynamic Weighting and Boundary-Aware Active Domain Adaptation for
Semantic Segmentation in Autonomous Driving Environment,
ITS(25), No. 11, November 2024, pp. 18461-18471.
IEEE DOI Code:
WWW Link.
2411
Semantic segmentation, Adaptation models, Uncertainty,
Autonomous vehicles, Labeling, Data models, Annotations,
semantic segmentation
BibRef
Li, W.[Wei],
Liao, M.[Muxin],
Hua, G.G.[Guo-Guang],
Zhang, Y.H.[Yu-Hang],
Zou, W.B.[Wen-Bin],
Contextual Guidance Network for Real-Time Semantic Segmentation of
Autonomous Driving,
ITS(26), No. 10, October 2025, pp. 16188-16203.
IEEE DOI Code:
WWW Link.
2511
Convolution, Computational modeling, Real-time systems,
Computational efficiency, Accuracy, Feature extraction,
feature fusion
BibRef
Liu, K.[Kunhua],
Zheng, Y.[Yi],
Xie, J.[Junkun],
Xie, Y.T.[Yu-Ting],
Wang, F.[Feiyang],
Ma, L.Y.[Long-Yan],
Dai, C.G.[Cheng-Gang],
Lu, T.[Tao],
Dynamic Scene Understanding for Autonomous Driving Using 2D-3D
Convolution With Voxel Key Points,
ITS(26), No. 10, October 2025, pp. 17562-17572.
IEEE DOI
2511
Feature extraction, Point cloud compression,
Semantic segmentation, Semantics, Convolution, autonomous driving
BibRef
Qiu, Y.[Yu],
Sun, Y.H.[Yu-Hang],
Mei, J.[Jie],
Xiao, L.[Lin],
Xu, J.[Jing],
Salient Object Detection in Traffic Scene Through the TSOD10K Dataset,
IP(34), 2025, pp. 7473-7488.
IEEE DOI Code:
WWW Link.
2511
Visualization, Videos, Vehicles, Accidents, Object detection, Semantics,
Transformers, Pedestrians, Benchmark testing, visual state space
BibRef
Yang, Y.Q.[Yi-Qian],
Sun, W.C.[Wei-Chao],
Real-Time Multispectral Semantic Segmentation Network Utilizing
Feature Frequency Decomposition and Spatial Division Distillation for
Autonomous Driving,
ITS(26), No. 11, November 2025, pp. 20363-20374.
IEEE DOI
2511
Feature extraction, Semantic segmentation, Lighting,
Real-time systems, Accuracy, Autonomous vehicles, Streaming media,
frequency
BibRef
Guo, S.[Sicen],
Long, Z.W.[Zi-Wei],
Wu, Z.Y.[Zhi-Yuan],
Chen, Q.J.[Qi-Jun],
Pitas, I.[Ioannis],
Fan, R.[Rui],
LIX: Implicitly Infusing Spatial Geometric Prior Knowledge Into
Visual Semantic Segmentation for Autonomous Driving,
IP(34), 2025, pp. 7250-7263.
IEEE DOI Code:
WWW Link.
2511
Knowledge engineering, Heuristic algorithms,
Semantic segmentation, Feature extraction, Visualization, Europe,
knowledge distillation
BibRef
Ren, Y.L.[Yi-Long],
Wang, L.[Lening],
Li, M.[Minda],
Jiang, H.[Han],
Cui, Z.Y.[Zhi-Yong],
Yang, M.M.[Meng-Meng],
Yu, H.Y.[Hai-Yang],
Yang, D.[Diange],
RM2Occ: Re-Projection Multi-Task Multi-Sensor Fusion for Autonomous
Driving 3D Object Detection and Occupancy Perception,
ITS(26), No. 11, November 2025, pp. 20864-20881.
IEEE DOI
2511
Semantic segmentation, Autonomous vehicles, Semantics,
Object detection, Laser radar, Point cloud compression
BibRef
Maag, K.[Kira],
Fischer, A.[Asja],
Uncertainty-weighted Loss Functions for Improved Adversarial Attacks
on Semantic Segmentation,
WACV24(3894-3902)
IEEE DOI
2404
Analytical models, Semantic segmentation, Perturbation methods,
Computational modeling, Artificial neural networks, Autonomous Driving
BibRef
Sodano, M.[Matteo],
Magistri, F.[Federico],
Nunes, L.[Lucas],
Behley, J.[Jens],
Stachniss, C.[Cyrill],
Open-World Semantic Segmentation Including Class Similarity,
CVPR24(3184-3194)
IEEE DOI Code:
WWW Link.
2410
Training, Semantic segmentation, Machine vision, Training data,
Data models, Autonomous Driving
BibRef
Zhou, B.[Brady],
Krähenbühl, P.[Philipp],
Cross-view Transformers for real-time Map-view Semantic Segmentation,
CVPR22(13750-13759)
IEEE DOI
2210
Convolutional codes, Image segmentation, Navigation, Semantics,
Transformers, Navigation and autonomous driving
BibRef
Jiang, T.J.[Tian-Jiao],
Jin, Y.[Yi],
Liang, T.F.[Teng-Fei],
Wang, X.[Xu],
Li, Y.D.[Yi-Dong],
Boundary Corrected Multi-Scale Fusion Network for Real-Time Semantic
Segmentation,
ICIP22(1886-1890)
IEEE DOI
2211
Image resolution, Computational modeling, Roads, Semantics,
Feature extraction, Real-time systems, Semantic segmentation, Boundary loss
BibRef
Iqbal, J.,
Ali, M.,
MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with
Spatially Independent and Semantically Consistent Labeling,
WACV20(1853-1862)
IEEE DOI
2006
Semantics, Image segmentation, Adaptation models, Training,
Computational modeling, Task analysis, Roads
BibRef
Yang, M.,
Yu, K.,
Zhang, C.,
Li, Z.,
Yang, K.,
DenseASPP for Semantic Segmentation in Street Scenes,
CVPR18(3684-3692)
IEEE DOI
1812
Convolution, Semantics, Image resolution, Kernel, Image segmentation,
Neurons, Autonomous vehicles
BibRef
Siam, M.,
Gamal, M.,
Abdel-Razek, M.,
Yogamani, S.,
Jagersand, M.,
RTSeg: Real-Time Semantic Segmentation Comparative Study,
ICIP18(1603-1607)
IEEE DOI
1809
Convolution, Semantics, Decoding,
Feature extraction, Benchmark testing, Real-time systems, realtime,
benchmarking framework
BibRef
Siam, M.,
Gamal, M.,
Abdel-Razek, M.,
Yogamani, S.,
Jagersand, M.,
Zhang, H.,
A Comparative Study of Real-Time Semantic Segmentation for Autonomous
Driving,
ECVW18(700-70010)
IEEE DOI
1812
Convolution, Semantics, Decoding,
Context modeling, Real-time systems, Image segmentation
BibRef
He, Y.[Yang],
Keuper, M.[Margret],
Schiele, B.[Bernt],
Fritz, M.[Mario],
Learning Dilation Factors for Semantic Segmentation of Street Scenes,
GCPR17(41-51).
Springer DOI
1711
BibRef
Zhu, S.Q.[Sheng-Qi],
Yang, Y.Q.[Yi-Qing],
Zhang, L.[Li],
From Label Maps to Label Strokes:
Semantic Segmentation for Street Scenes from Incomplete Training Data,
CVCP13(468-475)
IEEE DOI
1403
data handling
BibRef
Zhang, H.H.[Hong-Hui],
Xiao, J.X.[Jian-Xiong],
Quan, L.[Long],
Supervised Label Transfer for Semantic Segmentation of Street Scenes,
ECCV10(V: 561-574).
Springer DOI
1009
Set of labelled images of street scenes. Recognition is by matching
at image level, then using the given lables.
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Domain Adaption for Semantic Segmentation .