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Autonomous driving systems rely on panoptic driving perception that requires both precision and real-time performance.
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2014
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R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Region-based convolutional networks for accurate object detection and segmentation,” IEEE transactions on pattern analysis and machine intelligence , vol. 38, no. 1, pp. 142–158, 2015
2015
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J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 3431–3440
2015
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2016
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2017
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2017
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H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia, “Pyramid scene parsing network,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 2881–2890
2017
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T.-Y. Lin, P. Goyal, R. Girshick, K. He, and P. Dollár, “Focal loss for dense object detection,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 2980–2988
2017
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S. S. M. Salehi, D. Erdogmus, and A. Gholipour, “Tversky loss function for image segmentation using 3d fully convolutional deep networks,” in International Workshop on Machine Learning in Medical Imaging . Springer, 2017, pp. 379–387
2017
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J. Hu, L. Shen, and G. Sun, “Squeeze-and-excitation networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 7132–7141
2018
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I. Yaqoob, L. U. Khan, S. A. Kazmi, M. Imran, N. Guizani, and C. S. Hong, “Autonomous driving cars in smart cities: Recent advances, requirements, and challenges,” IEEE Network , vol. 34, no. 1, pp. 174–181, 2019
2019
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Z. Ouyang, J. Niu, Y. Liu, and M. Guizani, “Deep cnn-based real-time traffic light detector for self-driving vehicles,” IEEE Transactions on Mobile Computing , vol. 19, no. 2, pp. 300–313, 2019
2019
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Y. Hou, Z. Ma, C. Liu, and C. C. Loy, “Learning lightweight lane detection cnns by self attention distillation,” in Proceedings of the IEEE/CVF international conference on computer vision , 2019, pp. 1013–1021
2019
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H. Rezatofighi, N. Tsoi, J. Gwak, A. Sadeghian, I. Reid, and S. Savarese, “Generalized intersection over union: A metric and a loss for bounding box regression,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern recognition , 2019, pp. 658–666
2019
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F. Yu, H. Chen, X. Wang, W. Xian, Y. Chen, F. Liu, V. Madhavan, and T. Darrell, “Bdd100k: A diverse driving dataset for heterogeneous multitask learning,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 2636–2645
2020
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N. Carion, F. Massa, G. Synnaeve, N. Usunier, A. Kirillov, and S. Zagoruyko, “End-to-end object detection with transformers,” in European conference on computer vision . Springer, 2020, pp. 213–229
B. Cheng, I. Misra, A. G. Schwing, A. Kirillov, and R. Girdhar, “Masked-attention mask transformer for universal image segmentation,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2022, pp. 1290–1299
2022
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J. Guo, J. Wang, H. Wang, B. Xiao, Z. He, and L. Li, “Research on road scene understanding of autonomous vehicles based on multi-task learning,” Sensors , vol. 23, no. 13, p. 6238, 2023
2023
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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
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J. Zhan, Y. Luo, C. Guo, Y. Wu, J. Meng, and J. Liu, “Yolopx: Anchor-free multi-task learning network for panoptic driving perception,” Pattern Recognition , vol. 148, p. 110152, 2024
2024
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2020
Cited alongside, same era.
2020
Cited alongside, same era.
S. Vandenhende, S. Georgoulis, W. Van Gansbeke, M. Proesmans, D. Dai, and L. Van Gool, “Multi-task learning for dense prediction tasks: A survey,” IEEE transactions on pattern analysis and machine intelligence , vol. 44, no. 7, pp. 3614–3633, 2021
2021
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W. Zhang, K. Wang, Y. Wang, L. Yan, and F.-Y. Wang, “A loss-balanced multi-task model for simultaneous detection and segmentation,” Neurocomputing , vol. 428, pp. 65–78, 2021
2021
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K. Ishihara, A. Kanervisto, J. Miura, and V. Hautamaki, “Multi-task learning with attention for end-to-end autonomous driving,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 2902–2911
2021
Cited alongside, same era.
B. Cheng, A. Schwing, and A. Kirillov, “Per-pixel classification is not all you need for semantic segmentation,” Advances in neural information processing systems , vol. 34, pp. 17 864–17 875, 2021
2021
Cited alongside, same era.
D. Wu, M.-W. Liao, W.-T. Zhang, X.-G. Wang, X. Bai, W.-Q. Cheng, and W.-Y. Liu, “Yolop: You only look once for panoptic driving perception,” Machine Intelligence Research , vol. 19, no. 6, pp. 550–562, 2022
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
J. Wang, Q. J. Wu, and N. Zhang, “You only look at once for real-time and generic multi-task,” IEEE Transactions on Vehicular Technology , 2024
2024
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P. Hu, Y. Qian, T. Zheng, A. Li, Z. Chen, Y. Gao, X. Cheng, and J. Luo, “t-readi: Transformer-powered robust and efficient multimodal inference for autonomous driving,” IEEE Transactions on Mobile Computing , 2024
2024
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E. J. Roh, H. Baek, D. Kim, and J. Kim, “Fast quantum convolutional neural networks for low-complexity object detection in autonomous driving applications,” IEEE Transactions on Mobile Computing , 2024
2024
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Y. Zhao, W. Lv, S. Xu, J. Wei, G. Wang, Q. Dang, Y. Liu, and J. Chen, “Detrs beat yolos on real-time object detection,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2024, pp. 16 965–16 974
2024
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Z. Li, W. Liu, Z. Xie, X. Kang, P. Duan, and S. Li, “Faa-det: Feature augmentation and alignment for anchor-free oriented object detection,” IEEE Transactions on Geoscience and Remote Sensing , 2024
2024
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L. Fang, S. Bowen, M. Jianxi, and S. Weixing, “Yolomh: You only look once for multi-task driving perception with high efficiency,” Machine Vision and Applications , vol. 35, no. 3, p. 44, 2024
2024
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Y. Hao, J. Wu, Y. Yao, and Y. Guo, “A robust anchor-free detection method for sar ship targets with lightweight cnn,” IEEE Transactions on Instrumentation and Measurement , 2025
2025
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