FVNet: 3D Front-View Proposal Generation for Real-Time Object Detection from Point Clouds

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C. Sprunk, G. D. Tipaldi, A. Cherubini, and W. Burgard, “Lidar-based teach-and-repeat of mobile robot trajectories,” in IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2013, pp. 3144–3149

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S. Ren, K. He, R. Girshick, and J. Sun, “Faster r-cnn: Towards real-time object detection with region proposal networks,” in Advances in Neural Information Processing Systems , 2015, pp. 91–99

2015

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X. Chen, K. Kundu, Z. Zhang, H. Ma, S. Fidler, and R. Urtasun, “Monocular 3d object detection for autonomous driving,” in IEEE Conference on Computer Vision and Pattern Recognition . IEEE, 2016, pp. 2147–2156

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K. He, X. Zhang, S. Ren, and J. Sun, “Identity mappings in deep residual networks,” in European Conference on Computer Vision . Springer, 2016, pp. 630–645

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M. Engelcke, D. Rao, D. Z. Wang, C. H. Tong, and I. Posner, “Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks,” in IEEE International Conference on Robotics and Automation . IEEE, 2017, pp. 1355–1361

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Y. Zeng, Y. Hu, S. Liu, J. Ye, Y. Han, X. Li, and N. Sun, “Rt3d: Real-time 3-d vehicle detection in lidar point cloud for autonomous driving,” IEEE Robotics and Automation Letters , vol. 3, no. 4, pp. 3434–3440, 2018

2018

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M. Simon, S. Milz, K. Amende, and H.-M. Gross, “Complex-yolo: An euler-region-proposal for real-time 3d object detection on point clouds,” in European Conference on Computer Vision . Springer, 2018, pp. 197–209

2018

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K. Minemura, H. Liau, A. Monrroy, and S. Kato, “Lmnet: Real-time multiclass object detection on cpu using 3d lidar,” in Asia-Pacific Conference on Intelligent Robot Systems . IEEE, 2018, pp. 28–34

2018

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C. R. Qi, W. Liu, C. Wu, H. Su, and L. J. Guibas, “Frustum pointnets for 3d object detection from rgb-d data,” in IEEE Conference on Computer Vision and Pattern Recognition . IEEE, 2018, pp. 918–927

2018

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