点云识别-Learning to Sample
Learning to Sample 2019 CVPR 摘要 原文 译文 Processing large point clouds is a challenging task. Therefore, the data is often sampled to a size that can be processed more easily. 处理大规模点云是一项具有挑战性的任务，因此，一般把点云
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相关文章
- 1. 点云识别-Learning to Sample
- 2. 【点云识别】Learning to Segment 3D Point Clouds in 2D Image Space (CVPR 2020)
- 3. Learning to Learn: Meta-Critic Networks for Sample Efficient Learning||论文讲解
- 4. 【点云识别】Grid-GCN for Fast and Scalable Point Cloud Learning (CVPR 2020)
- 5. 【点云识别】Unsupervised Learning of Intrinsic Structural Representation Points(CVPR 2020)
- 6. 虹软人脸识别Android Sample Code
- 7. 【点云识别】D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features(CVPR 2020 Oral)
- 8. 【点云识别】Mapping in a Cycle: Sinkhorn Regularized Unsupervised Learning for Point Cloud Shapes ECCV2020
- 9. 3D点云目标识别和抓取
- 10. 【点云识别】Weakly Supervised Semantic Point Cloud Segmentation: Towards 10x Fewer Labels(CVPR 2020)