Citation: | YUE Yuanchen, CAI Yunfei, WANG Dongsheng, “GridNet-3D: A Novel Real-Time 3D Object Detection Algorithm Based on Point Cloud,” Chinese Journal of Electronics, vol. 30, no. 5, pp. 931-939, 2021, doi: 10.1049/cje.2021.07.004 |
Dong R, Jin L, Wu H., "Viewpoint optimization method for flying robot inspecting transmission towers based on point cloud model", Chinese Journal of Electronics, Vol.27, No.5, pp.976-984, 2018.
|
Qi C R, Su H, Mo K, et al., "Pointnet:Deep learning on point sets for 3d classification and segmentation", IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, Hawaii, USA, pp.652-660, 2017.
|
Ren S, He K, Girshick R, et al., "Faster R-CNN:Towards real-time object detection with region proposal networks", Advances in Neural Information Processing Systems, Montreal, Quebec, Canada, pp.91-99, 2015.
|
Zhou Y and Tuzel O., "Voxelnet:End-to-end learning for point cloud based 3D object detection", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Utah, USA, pp.4490-4499, 2018.
|
Geiger A, Lenz P and Urtasun R., "Are we ready for autonomous driving? The kitti vision benchmark suite", IEEE Conference on Computer Vision and Pattern Recognition, Providence, Rhode Island, USA, pp.3354-3361, 2012.
|
Maturana D and Scherer S., "Voxnet:A 3D convolutional neural network for real-time object recognition", IEEE International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, pp.922-928, 2015.
|
Qi C R, Su H, Nießner M, et al., "Volumetric and multiview cnns for object classification on 3D data", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, USA, pp.5648-5656, 2016.
|
Li Y, Pirk S, Su H, et al., "FPNN:Field probing neural networks for 3d data", Advances in Neural Information Processing Systems, Barcelona, Spain, pp.307-315, 2016.
|
Qi C R, Yi L, Su H, et al., "Pointnet++:Deep hierarchical feature learning on point sets in a metric space", Advances in Neural Information Processing Systems, Long Beach, CA, USA, pp.5099-5108, 2017.
|
Xu D, Anguelov D and Jain A., "Pointfusion:Deep sensor fusion for 3D bounding box estimation", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Istanbul, Turkey, pp.244-253, 2018.
|
He K, Zhang X, Ren S, et al., "Deep residual learning for image recognition", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, Nevada, USA, pp.770-778, 2016.
|
Qi C R, Liu W, Wu C, et al., "Frustum pointnets for 3D object detection from RGB-D data", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Utah, USA, pp.918-927, 2018.
|
Yan Y, Mao Y and Li B., "Second:Sparsely embedded convolutional detection", Sensors, Vol.18, No.10, pp.33-37, 2018.
|
Ai Ali W, Abdelkarim S, Zahran M, et al., "YOLO3D:Endtoend real-time 3D oriented object bounding box detection from LiDAR point cloud", European Conference on Computer Vision, Munich, Germany, pp.442-450, 2018.
|
Beltran J, Guindel C, Moreno F M, et al., "BirdNet:A 3D object detection framework from LiDAR information", International Conference on Intelligent Transportation Systems (ITSC), Honolulu, Hawaii, USA, pp.3517-3523, 2018.
|
Liu W, Anguelov D, Erhan D, et al., "SSD:Single shot multibox detector", European Conference on Computer Vision, Amsterdam, Holland, pp.21-37, 2016.
|
Girshick R., "Fast R-CNN", Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile, pp.1440-1448, 2015.
|
Lin T Y, Goyal P, Girshick R, et al., "Focal loss for dense object detection", Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, pp.2980-2988, 2017.
|
Li B, Zhang T and Xia T., "Vehicle detection from 3d lidar using fully convolutional network", https://arxiv.org/abs/1608.07916,2016-8-29.
|
Chen X, Ma H, Wan J, et al., "Multi-view 3D object detection network for autonomous driving", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, Hawaii, USA, pp.1907-1915, 2017.
|
M. Liang M, Yang B, Wang S, et al., "Deep continuous fusion for multi-sensor 3D object detection", Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany, pp.641-656, 2018.
|
S Shin K, Kwon Y P and Tomizuka M., "Roarnet:A robust 3D object detection based on region approximation refinement", Intelligent Vehicles Symposium (IV), Paris, France, pp.2510-2515, 2019.
|
Wang D Z and Posner I., "Voting for voting in online point cloud object detection", Robotics:Science and Systems, pp.1156-1165, 2015.
|