【點雲識別】Mapping in a Cycle: Sinkhorn Regularized Unsupervised Learning for Point Cloud Shapes ECCV2020
Mapping in a Cycle: Sinkhorn Regularized Unsupervised Learning for Point Cloud Shapes 本文介紹一篇ECCV2020裏面關於點雲無監督學習的文章。 論文 目前還沒有開源代碼 1. 問題 點雲形狀的無監督學習 2. 思想 本文的主體思路是延續 Unsupervised cycle-consistent deforma
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- 1. 【點雲識別】PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding (ECCV 2020)
- 2. 【點雲識別】Grid-GCN for Fast and Scalable Point Cloud Learning (CVPR 2020)
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- 9. 【點雲識別】Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud(CVPR 2020)
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相關文章
- 1. 【點雲識別】PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding (ECCV 2020)
- 2. 【點雲識別】Grid-GCN for Fast and Scalable Point Cloud Learning (CVPR 2020)
- 3. 【點雲識別】A Closer Look at Local Aggregation Operators in Point Cloud Analysis (ECCV 2020)
- 4. 點雲識別-Learning to Sample
- 5. 3D 點雲識別: Geometric Feedback Network for Point Cloud Classification
- 6. 【點雲識別】Learning to Segment 3D Point Clouds in 2D Image Space (CVPR 2020)
- 7. Point Encoder GAN: A deep learning model for 3D point cloud inpainting
- 8. Point Cloud 2019
- 9. 【點雲識別】Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud(CVPR 2020)
- 10. 【點雲識別】Adaptive Hierarchical Down-Sampling for Point Cloud Classification(CVPR 2020)