CVPR2019| 05-20更新17篇点云相关论文及代码合集

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前段时间，计算机视觉顶会CVPR 2019 公布了接收结果，极市也对此做了相关报道：1300篇！CVPR2019接收结果公布，你中了吗？。目前官方已公布了接收论文列表，极市已汇总目前公开的所有论文链接及code（目前已更新632篇），今日更新论文如下：

CVPR2019 全部论文汇总：

https://github.com/extreme-assistant/cvpr2019

CVPR2019 论文解读

http://bbs.cvmart.net/topics/287/cvpr2019

1.Graph Attention Convolution for Point Cloud Segmentation
作者：待更新
论文链接：https://engineering.purdue.edu/~jshan/publications/2018/Lei%20Wang%20Graph%20Attention%20Convolution%20for%20Point%20Cloud%20Segmentation%20CVPR2019.pdf

2.GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud
作者：Li Yi, Wang Zhao, He Wang, Minhyuk Sung, Leonidas Guibas
论文链接：https://arxiv.org/abs/1812.03320

3.Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks
作者：Yizhak Ben-Shabat, Michael Lindenbaum, Anath Fischer
论文链接：https://arxiv.org/abs/1812.00709 
源码链接：https://github.com/sitzikbs/Nesti-Net

4.Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes
作者：Ziquan Lan, Zi Jian Yew，Gim Hee Lee
论文链接：https://www.researchgate.net/publication/332240602_Robust_Point_Cloud_Based_Reconstruction_of_Large-Scale_Outdoor_Scenes 
源码链接：https://github.com/ziquan111/RobustPCLReconstruction

5.PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
作者：Yasuhiro Aoki, Hunter Goforth, Rangaprasad Arun Srivatsan, Simon Lucey
论文链接：https://arxiv.org/abs/1903.05711 
源码链接：https://github.com/hmgoforth/PointNetLK

6.PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing
作者：Hengshuang Zhao， Li Jiang， Chi-Wing Fu，Jiaya Jia
论文链接：http://jiaya.me/papers/pointweb_cvpr19.pdf

7.ClusterNet: Deep Hierarchical Cluster Network with Rigorously Rotation-Invariant Representation for Point Cloud Analysis
作者：Chao Chen， Guanbin Li， Ruijia Xu， Tianshui Chen， Meng Wang， Liang Lin
论文链接：http://www.linliang.net/wp-content/uploads/2019/04/CVPR2019_PointClound.pdf

8.FilterReg: Robust and Efficient Probabilistic Point-Set Registration using Gaussian Filter and Twist Parameterization
作者：Wei Gao, Russ Tedrake
论文链接：https://arxiv.org/abs/1811.10136 
源码链接：https://bitbucket.org/gaowei19951004/poser/src/master/

9.Embodied Question Answering in Photorealistic Environments with Point Cloud Perception
作者：Erik Wijmans, Samyak Datta, Oleksandr Maksymets, Abhishek Das, Georgia Gkioxari, Stefan Lee, Irfan Essa, Devi Parikh, Dhruv Batra
论文链接：https://arxiv.org/abs/1904.03461

10.SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences
作者：Huu Le, Thanh-Toan Do, Tuan Hoang, Ngai-Man Cheung
论文链接：https://arxiv.org/abs/1904.03483
源码链接：https://github.com/intellhave/SDRSAC （matlab）

11.PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds
作者：Aseem Behl, Despoina Paschalidou, Simon Donné, Andreas Geiger
论文链接：https://arxiv.org/abs/1806.02170
源码链接：https://github.com/aseembehl/pointflownet

12.PointPillars: Fast Encoders for Object Detection from Point Clouds
作者：Alex H. Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, Oscar Beijbom
论文链接：https://arxiv.org/abs/1812.05784
源码链接：https://github.com/nutonomy/second.pytorch

13.PointNetLK: Point Cloud Registration using PointNet
作者：Yasuhiro Aoki, Hunter Goforth, Rangaprasad Arun Srivatsan, Simon Lucey
论文链接：https://arxiv.org/abs/1903.05711
源码链接：https://github.com/hmgoforth/PointNetLK

14.Supervised Fitting of Geometric Primitives to 3D Point Clouds（Oral）
作者：Lingxiao Li, Minhyuk Sung, Anastasia Dubrovina, Li Yi, Leonidas Guibas
论文链接：https://arxiv.org/abs/1811.08988
源码链接：https://github.com/csimstu2/SPFN

15.PointConv: Deep Convolutional Networks on 3D Point Clouds
作者：Wenxuan Wu, Zhongang Qi, Li Fuxin
论文链接：https://arxiv.org/abs/1811.07246
源码链接：https://github.com/DylanWusee/pointconv

16.Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling
作者：Jiancheng Yang, Qiang Zhang, Bingbing Ni, Linguo Li, Jinxian Liu, Mengdie Zhou, Qi Tian
论文链接：https://arxiv.org/abs/1904.03375v1

17.Spherical Fractal Convolutional Neural Networks for Point Cloud Recognition
作者：Yongming Rao, Jiwen Lu, Jie Zhou
论文链接：https://raoyongming.github.io/files/SFCNN.pdf