Publisher
Springer Science and Business Media LLC
Reference35 articles.
1. Li, H.T., Todd, Z., Bielski, N., Carroll, F.: 3D lidar point-cloud projection operator and transfer machine learning for effective road surface features detection and segmentation. Vis. Comput. 38(5), 1759–1774 (2022)
2. Nezhadarya, E., Taghavi, E., Razani, R., Liu, B., Luo, J.: Adaptive hierarchical down-sampling for point cloud classification. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 12956–12964 (2020)
3. Wang, X., Jin, Y., Cen, Y., Lang, C., Li, Y.: PST-NET: point cloud sampling via point-based transformer. In: Image and graphics: 11th international conference, ICIG 2021, Haikou, China, August 6–8, 2021, Proceedings, Part III 11, Springer, pp. 57–69 (2021)
4. Qi, C.R., Yi, L., Su, H., Guibas, L.J.: PointNet++: deep hierarchical feature learning on point sets in a metric space. Adv. Neural Inf. Process. Syst. 30 (2017)
5. Dovrat, O., Lang, I., Avidan, S.: Learning to sample. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 2760–2769 (2019)