【点云识别】Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels(CVPR 2020)
Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels 本文介绍一篇cvpr2020里面关于点云弱监督分割的文章。 论文 目前还没有开源代码 1. 问题 点云的弱监督分割 2. 思想 根据弱监督的特点，提出了incomplete supervision branch 和 inexact superv
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- 3. [点云分割]-Multi-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point Clouds
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相关文章
- 1. 【点云语义分割】Weakly Supervised Semantic Point Cloud Segmentation: Towards 10× Fewer Labels（CVPR 2020）
- 2. 【点云识别】Multi-Path Region Mining ForWeakly Supervised 3D Semantic Segmentation on Point Clouds
- 3. [点云分割]-Multi-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point Clouds
- 4. Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation
- 5. Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach(AAAI 2020)
- 6. 【点云识别】PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation (CVPR 2020)
- 7. 【点云识别】3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation (CVPR 2020)
- 8. [点云识别]-SegGCN: Efficient 3D Point Cloud Segmentation with Fuzzy Spherical Kernel
- 9. 【点云语义分割】Multi-Path Region Mining ForWeakly Supervised 3D Semantic Segmentation on Point Clouds（CVPR）
- 10. 《Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation》笔记