Overview to Samplenet Differentiable Point Cloud Sampling
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History
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PointASNL: Robust Point Clouds Processing Using Nonlocal Neural Networks With Adaptive Sampling
Adaptive Hierarchical Down-Sampling for Point Cloud Classification
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver (6-min video)
Unsupervised Learning of Shape and Pose with Differentiable Point Clouds
Maximum Leverage Sampling for the selection of correspondences (synthetic point cloud)
Shai Avidan: Learning to Sample
E20 Guocheng Qian PU GCN Point Cloud Upsampling using Graph Convolutional Networks
[CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap
Differentiable DAG Sampling
Point Cloud Upsampling via Disentangled Refinement. CVPR 2021
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Last Updated: October 20, 2026
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Summary
Authors: Itai Lang, Asaf Manor, Shai Avidan Description: There is a growing number of tasks that work directly on Itai Lang, Oren Dovrat, Asaf Manor, Shai Avidan, Tel Aviv University Israel Computer Vision Day 2019 6.1.20. In this episode of the Talking Papers Podcast, I hosted Itai Lang to chat about his paper " Authors: Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, Shuguang Cui Description: Raw Authors: Ehsan Nezhadarya, Ehsan Taghavi, Ryan Razani, Bingbing Liu, Jun Luo Description: Deterministic down- Authors: Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, Andrew Markham Description: ... NeurIPS 2021 Oral paper. Shape-As- Unsupervised Learning of Shape and Pose with For details see: Glira Philipp, Pfeifer Norbert, Briese Christian, Ressl Camillo: A Correspondence Framework for ALS Strip ... To do that, we introduce a novel This is the full video for our ICLR 2022 paper " Supplemental video for our CVPR2021 Paper: "
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