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Recent advancements in high-definition \emph{HD} map construction have demonstrated the effectiveness of dense representations, which heavily rely on computationally intensive bird's-eye view \emph{BEV} features.
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G. Xue, J. Wei, R. Li, and J. Cheng, “Lego-loam-sc: An improved simultaneous localization and mapping method fusing lego-loam and scan context for underground coalmine,” Sensors , vol. 22, no. 2, p. 520, 2022
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Y. Li, Z. Ge, G. Yu, J. Yang, Z. Wang, Y. Shi, J. Sun, and Z. Li, “Bevdepth: Acquisition of reliable depth for multi-view 3d object detection,” in Proceedings of the AAAI Conference on Artificial Intelligence , vol. 37, no. 2, 2023, pp. 1477–1485
2023
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2023
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2023
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2023
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2022
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Z. Li, W. Wang, H. Li, E. Xie, C. Sima, T. Lu, Y. Qiao, and J. Dai, “Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,” in European conference on computer vision . Springer, 2022, pp. 1–18
2022
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2022
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2022
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2022
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F. Li, H. Zhang, S. Liu, J. Guo, L. M. Ni, and L. Zhang, “Dn-detr: Accelerate detr training by introducing query denoising,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2022, pp. 13 619–13 627
2022
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Z. Tian, X. Chu, X. Wang, X. Wei, and C. Shen, “Fully convolutional one-stage 3d object detection on lidar range images,” Advances in Neural Information Processing Systems , vol. 35, pp. 34 899–34 911, 2022
2022
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2022
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2022
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2023
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S. Wang, Y. Liu, T. Wang, Y. Li, and X. Zhang, “Exploring object-centric temporal modeling for efficient multi-view 3d object detection,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 3621–3631
2023
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2024
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2024
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T. Yuan, Y. Liu, Y. Wang, Y. Wang, and H. Zhao, “Streammapnet: Streaming mapping network for vectorized online hd map construction,” in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , 2024, pp. 7356–7365
2024
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Z. Sun, Z. Wang, L. Halilaj, and J. Luettin, “Semanticformer: Holistic and semantic traffic scene representation for trajectory prediction using knowledge graphs,” IEEE Robotics and Automation Letters , vol. 9, no. 9, pp. 7381–7388, 2024
2024
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2024
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