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High precision, lightweight, and real-time responsiveness are three essential requirements for implementing autonomous driving.
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2018
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C.-Y. Wang, A. Bochkovskiy, and H.-Y. M. Liao, “Scaled-yolov4: Scaling cross stage partial network,” in Proceedings of the IEEE/cvf conference on computer vision and pattern recognition , 2021, pp. 13 029–13 038
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2018
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Z. Cai and N. Vasconcelos, “Cascade r-cnn: Delving into high quality object detection,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2018, pp. 6154–6162
2018
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2019
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J. Pang, K. Chen, J. Shi, H. Feng, W. Ouyang, and D. Lin, “Libra r-cnn: Towards balanced learning for object detection,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2019, pp. 821–830
2019
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2020
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2020
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S. Fan, F. Zhu, S. Chen, H. Zhang, B. Tian, Y. Lv, and F.-Y. Wang, “Fii-centernet: an anchor-free detector with foreground attention for traffic object detection,” IEEE Transactions on Vehicular Technology , vol. 70, no. 1, pp. 121–132, 2021
2021
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Y. Cai, T. Luan, H. Gao, H. Wang, L. Chen, Y. Li, M. A. Sotelo, and Z. Li, “Yolov4-5d: An effective and efficient object detector for autonomous driving,” IEEE Transactions on Instrumentation and Measurement , vol. 70, pp. 1–13, 2021
2021
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J. Zhao, D. Wu, Z. Yu, and Z. Gao, “Drmnet: A multi-task detection model based on image processing for autonomous driving scenarios,” IEEE Transactions on Vehicular Technology , 2023
2023
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Y. Guo, R. W. Liu, Y. Lu, J. Nie, L. Lyu, Z. Xiong, J. Kang, H. Yu, and D. Niyato, “Haze visibility enhancement for promoting traffic situational awareness in vision-enabled intelligent transportation,” IEEE Transactions on Vehicular Technology , 2023
2023
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H. Wang, Y. Xu, Z. Wang, Y. Cai, L. Chen, and Y. Li, “Centernet-auto: A multi-object visual detection algorithm for autonomous driving scenes based on improved centernet,” IEEE Transactions on Emerging Topics in Computational Intelligence , 2023
2023
Closest in time.
C.-Y. Wang, A. Bochkovskiy, and H.-Y. M. Liao, “Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 7464–7475
2023
Closest in time.
S. Miraliev, S. Abdigapporov, V. Kakani, and H. Kim, “Real-time memory efficient multitask learning model for autonomous driving,” IEEE Transactions on Intelligent Vehicles , 2023
2023
Closest in time.
H. Wang, M. Qiu, Y. Cai, L. Chen, and Y. Li, “Sparse u-pdp: A unified multi-task framework for panoptic driving perception,” IEEE Transactions on Intelligent Transportation Systems , 2023
2023
Closest in time.
Z. Zou, K. Chen, Z. Shi, Y. Guo, and J. Ye, “Object detection in 20 years: A survey,” Proceedings of the IEEE , 2023
2023
Closest in time.