2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds-Reference-Cited by-同舟云学术

2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds

Published:2022 Issue: Volume: Page:677-695
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Yan Xu,Gao Jiantao,Zheng Chaoda,Zheng Chao,Zhang Ruimao,Cui Shuguang,Li Zhen

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-19815-1_39

Reference68 articles.

1. Hu, Q., et al.: Randla-net: efficient semantic segmentation of large-scale point clouds. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2020)

2. Yan, X., et al.: Sparse single sweep lidar point cloud segmentation via learning contextual shape priors from scene completion. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 3101–3109 (2021)

3. Graham, B., Engelcke, M., van der Maaten, L.: 3D semantic segmentation with submanifold sparse convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9224–9232 (2018)

4. Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834–848 (2017)

5. Chen, L.C., Papandreou, G., Schroff, F., Adam, H.: Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587 (2017)

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