[點雲識別]-SegGCN: Efficient 3D Point Cloud Segmentation with Fuzzy Spherical Kernel
SegGCN: Efficient 3D Point Cloud Segmentation with Fuzzy Spherical Kernel 摘要 Fuzzy kernel SegGCN 實驗部分 kernel compare Robustness to point density (missing data) Decoder module choice CVPR 2020 主要是由2019
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相關文章
- 1. [點雲識別]-SegGCN: Efficient 3D Point Cloud Segmentation with Fuzzy Spherical Kernel
- 2. 【點雲識別】PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation (CVPR 2020)
- 3. 【點雲識別】Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels(CVPR 2020)
- 4. 【點雲識別】PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding (ECCV 2020)
- 5. 【點雲識別】Multi-Path Region Mining ForWeakly Supervised 3D Semantic Segmentation on Point Clouds
- 6. Point Cloud 2019
- 7. 3D點雲網絡：PointNet:Deep Learning on Point Sets for 3D Classification and Segmentation
- 8. 3D Recurrent Neural Networks with Context Fusion for Point Cloud Semantic Segmentation[ECCV2018]
- 9. 3D 點雲識別: Geometric Feedback Network for Point Cloud Classification
- 10. 點雲識別-Learning to Sample