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3D Occupancy Network Modelling for Multi-view Image Fusion Techniques in Autonomous Driving

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Feb 05, 2025

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Cheng, J., Yin, W., Wang, K., Chen, X., Wang, S., & Yang, X. (2024). Adaptive fusion of single-view and multi-view depth for autonomous driving. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10138-10147). ChengJ.YinW.WangK.ChenX.WangS. & YangX. (2024). Adaptive fusion of single-view and multi-view depth for autonomous driving. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10138-10147). Search in Google Scholar

Cheng, Z., Li, H., Asano, Y., Zheng, Y., & Sato, I. (2021). Multi-view 3d reconstruction of a texture-less smooth surface of unknown generic reflectance. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 16226-16235). ChengZ.LiH.AsanoY.ZhengY. & SatoI. (2021). Multi-view 3d reconstruction of a texture-less smooth surface of unknown generic reflectance. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 16226-16235). Search in Google Scholar

Wang, Y., Guizilini, V. C., Zhang, T., Wang, Y., Zhao, H., & Solomon, J. (2022, January). Detr3d: 3d object detection from multi-view images via 3d-to-2d queries. In Conference on Robot Learning (pp. 180-191). PMLR. WangY.GuiziliniV. C.ZhangT.WangY.ZhaoH. & SolomonJ. (2022, January). Detr3d: 3d object detection from multi-view images via 3d-to-2d queries. In Conference on Robot Learning (pp. 180-191). PMLR. Search in Google Scholar

Heng, L., Choi, B., Cui, Z., Geppert, M., Hu, S., Kuan, B., ... & Sattler, T. (2019, May). Project autovision: Localization and 3d scene perception for an autonomous vehicle with a multi-camera system. In 2019 International Conference on Robotics and Automation (ICRA) (pp. 4695-4702). IEEE. HengL.ChoiB.CuiZ.GeppertM.HuS.KuanB. ... & SattlerT. (2019, May). Project autovision: Localization and 3d scene perception for an autonomous vehicle with a multi-camera system. In 2019 International Conference on Robotics and Automation (ICRA) (pp. 4695-4702). IEEE. Search in Google Scholar

Ma, X., Wang, Z., Li, H., Zhang, P., Ouyang, W., & Fan, X. (2019). Accurate monocular 3d object detection via color-embedded 3d reconstruction for autonomous driving. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 6851-6860). MaX.WangZ.LiH.ZhangP.OuyangW. & FanX. (2019). Accurate monocular 3d object detection via color-embedded 3d reconstruction for autonomous driving. In Proceedings of the IEEE/CVF international conference on computer vision (pp. 6851-6860). Search in Google Scholar

Rebecq, H., Gallego, G., Mueggler, E., & Scaramuzza, D. (2018). EMVS: Event-based multi-view stereo—3D reconstruction with an event camera in real-time. International Journal of Computer Vision, 126(12), 1394-1414. RebecqH.GallegoG.MuegglerE. & ScaramuzzaD. (2018). EMVS: Event-based multi-view stereo—3D reconstruction with an event camera in real-time. International Journal of Computer Vision, 126(12), 1394-1414. Search in Google Scholar

Zhu, Z., Zhang, Y., Chen, H., Dong, Y., Zhao, S., Ding, W., ... & Zheng, S. (2023). Understanding the Robustness of 3D Object Detection With Bird’s-Eye-View Representations in Autonomous Driving. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 21600-21610). ZhuZ.ZhangY.ChenH.DongY.ZhaoS.DingW. ... & ZhengS. (2023). Understanding the Robustness of 3D Object Detection With Bird’s-Eye-View Representations in Autonomous Driving. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 21600-21610). Search in Google Scholar

Boora, S., Sahu, B. C., & Patra, D. (2017, July). 3D image reconstruction from multiview images. In 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-7). IEEE. BooraS.SahuB. C. & PatraD. (2017, July). 3D image reconstruction from multiview images. In 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-7). IEEE. Search in Google Scholar

Shrestha, R., Fan, Z., Su, Q., Dai, Z., Zhu, S., & Tan, P. (2021, December). Meshmvs: multi-view stereo guided mesh reconstruction. In 2021 International Conference on 3D Vision (3DV) (pp. 1290-1300). IEEE. ShresthaR.FanZ.SuQ.DaiZ.ZhuS. & TanP. (2021, December). Meshmvs: multi-view stereo guided mesh reconstruction. In 2021 International Conference on 3D Vision (3DV) (pp. 1290-1300). IEEE. Search in Google Scholar

Jadhav, T., Singh, K., & Abhyankar, A. (2017). A review and comparison of multi-view 3D reconstruction methods. Journal of Engineering Research, 5(3). JadhavT.SinghK. & AbhyankarA. (2017). A review and comparison of multi-view 3D reconstruction methods. Journal of Engineering Research, 5(3). Search in Google Scholar

Gao, L., Zhao, Y., Han, J., & Liu, H. (2022). Research on multi-view 3D reconstruction technology based on SFM. Sensors, 22(12), 4366. GaoL.ZhaoY.HanJ. & LiuH. (2022). Research on multi-view 3D reconstruction technology based on SFM. Sensors, 22(12), 4366. Search in Google Scholar

Zhou, X., Lin, Z., Shan, X., Wang, Y., Sun, D., & Yang, M. H. (2024). Drivinggaussian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 21634-21643). ZhouX.LinZ.ShanX.WangY.SunD. & YangM. H. (2024). Drivinggaussian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 21634-21643). Search in Google Scholar

Li, Y., Ge, Z., Yu, G., Yang, J., Wang, Z., Shi, Y., ... & Li, Z. (2023, June). Bevdepth: Acquisition of reliable depth for multi-view 3d object detection. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 2, pp. 1477-1485). LiY.GeZ.YuG.YangJ.WangZ.ShiY. ... & LiZ. (2023, June). Bevdepth: Acquisition of reliable depth for multi-view 3d object detection. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 2, pp. 1477-1485). Search in Google Scholar

Chen, D., Li, J., Guizilini, V., Ambrus, R. A., & Gaidon, A. (2023). Viewpoint equivariance for multi-view 3d object detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9213-9222). ChenD.LiJ.GuiziliniV.AmbrusR. A. & GaidonA. (2023). Viewpoint equivariance for multi-view 3d object detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9213-9222). Search in Google Scholar

Li, S., Geng, K., Yin, G., Wang, Z., & Qian, M. (2023). MVMM: Multiview multimodal 3-D object detection for autonomous driving. IEEE Transactions on Industrial Informatics, 20(1), 845-853. LiS.GengK.YinG.WangZ. & QianM. (2023). MVMM: Multiview multimodal 3-D object detection for autonomous driving. IEEE Transactions on Industrial Informatics, 20(1), 845-853. Search in Google Scholar

Choi, H. M., Kang, H., & Hyun, Y. (2019, October). Multi-view reprojection architecture for orientation estimation. In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) (pp. 2357-2366). IEEE. ChoiH. M.KangH. & HyunY. (2019, October). Multi-view reprojection architecture for orientation estimation. In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) (pp. 2357-2366). IEEE. Search in Google Scholar

Zhao, J., Zhang, X. N., Gao, H., Yin, J., Zhou, M., & Tan, C. (2018, July). Object detection based on hierarchical multi-view proposal network for autonomous driving. In 2018 international joint conference on neural networks (IJCNN) (pp. 1-6). IEEE. ZhaoJ.ZhangX. N.GaoH.YinJ.ZhouM. & TanC. (2018, July). Object detection based on hierarchical multi-view proposal network for autonomous driving. In 2018 international joint conference on neural networks (IJCNN) (pp. 1-6). IEEE. Search in Google Scholar

Steffen, L., Ulbrich, S., Roennau, A., & Dillmann, R. (2019, December). Multi-view 3d reconstruction with self-organizing maps on event-based data. In 2019 19th International Conference on Advanced Robotics (ICAR) (pp. 501-508). IEEE. SteffenL.UlbrichS.RoennauA. & DillmannR. (2019, December). Multi-view 3d reconstruction with self-organizing maps on event-based data. In 2019 19th International Conference on Advanced Robotics (ICAR) (pp. 501-508). IEEE. Search in Google Scholar

Xiang, X., Wang, Z., Lao, S., & Zhang, B. (2020). Pruning multi-view stereo net for efficient 3D reconstruction. ISPRS Journal of Photogrammetry and Remote Sensing, 168, 17-27. XiangX.WangZ.LaoS. & ZhangB. (2020). Pruning multi-view stereo net for efficient 3D reconstruction. ISPRS Journal of Photogrammetry and Remote Sensing, 168, 17-27. Search in Google Scholar

Min, C., Xiao, L., Zhao, D., Nie, Y., & Dai, B. (2024). Multi-camera unified pre-training via 3d scene reconstruction. IEEE Robotics and Automation Letters. MinC.XiaoL.ZhaoD.NieY. & DaiB. (2024). Multi-camera unified pre-training via 3d scene reconstruction. IEEE Robotics and Automation Letters. Search in Google Scholar

Srivani B., Sandhya N. & Padmaja Rani B. (2023). Theoretical analysis and comparative study of top 10 optimization algorithms with DMS algorithm. Intelligent Decision Technologies(3),607-620. SrivaniB.SandhyaN. & Padmaja RaniB. (2023). Theoretical analysis and comparative study of top 10 optimization algorithms with DMS algorithm. Intelligent Decision Technologies(3),607-620. Search in Google Scholar

Quan Qiu,Zhengqiang Fan,Zhijun Meng,Qing Zhang,Yue Cong,Bin Li... & Chunjiang Zhao. (2018). Extended Ackerman Steering Principle for the coordinated movement control of a four wheel drive agricultural mobile robot. Computers and Electronics in Agriculture40-50. QiuQuanFanZhengqiangMengZhijunZhangQingCongYueLiBin... & ZhaoChunjiang. (2018). Extended Ackerman Steering Principle for the coordinated movement control of a four wheel drive agricultural mobile robot. Computers and Electronics in Agriculture40-50. Search in Google Scholar

Huaiyuan Xu, Junliang Chen, Shiyu Meng, Yi Wang & Lap Pui Chau. (2025). A survey on occupancy perception for autonomous driving: The information fusion perspective. Information Fusion102671-102671. XuHuaiyuanChenJunliangMengShiyuWangYi & ChauLap Pui. (2025). A survey on occupancy perception for autonomous driving: The information fusion perspective. Information Fusion102671-102671. Search in Google Scholar

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