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/cvpr201 9

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 

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