【点云识别】PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation (CVPR 2020)
PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation 本文介绍一篇cvpr2020里面关于点云实例分割的文章。 论文 目前还没有开源代码 1. 问题 和2D图片不同，3D点云不存在遮挡现象，存在大量的void space， 本文想充分利用void space 进行分割。 2. 思想 那么如何利用这些void space 呢
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相关文章
- 1. 【点云识别】3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation (CVPR 2020)
- 2. 【点云识别】Learning to Segment 3D Point Clouds in 2D Image Space (CVPR 2020)
- 3. CVPR 2020-Instance Segmentation（2020最新分割论文）
- 4. 【点云识别】Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels(CVPR 2020)
- 5. [点云识别]-SegGCN: Efficient 3D Point Cloud Segmentation with Fuzzy Spherical Kernel
- 6. 【点云识别】PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding (ECCV 2020)
- 7. 【点云识别】Grid-GCN for Fast and Scalable Point Cloud Learning (CVPR 2020)
- 8. 【点云识别】Adaptive Hierarchical Down-Sampling for Point Cloud Classification(CVPR 2020)
- 9. 【点云识别】AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss (CVPR 2020 oral)
- 10. [SGN]SGN: Sequential Grouping Networks for Instance Segmentation