Semi-automated Generation of Accurate Ground-Truth for 3D Object Detection
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-45725-8_2
Reference40 articles.
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2. Brazil, G., Liu, X.: M3D-RPN: monocular 3D region proposal network for object detection. In: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), pp. 9286–9295. IEEE Computer Society, Los Alamitos (2019). https://doi.ieeecomputersociety.org/10.1109/ICCV.2019.00938
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5. Chabot, F., Chaouch, M., Rabarisoa, J., Teulière, C., Chateau, T.: Deep MANTA: a coarse-to-fine many-task network for joint 2D and 3D vehicle analysis from monocular image. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1827–1836. IEEE Computer Society, Los Alamitos (2017). https://doi.ieeecomputersociety.org/10.1109/CVPR.2017.198
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