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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Dynamic Graph CNN for Learning on Point Clouds
Yue Wang, Yongbin Sun, Ziwei Liu, et al.
ACM Transactions on Graphics (2019) Vol. 38, Iss. 5, pp. 1-12
Open Access | Times Cited: 5237

Showing 1-25 of 5237 citing articles:

Graph neural networks: A review of methods and applications
Jie Zhou, Ganqu Cui, Shengding Hu, et al.
AI Open (2020) Vol. 1, pp. 57-81
Open Access | Times Cited: 3796
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu, Shirui Pan, Fengwen Chen, et al.
IEEE Transactions on Neural Networks and Learning Systems (2020) Vol. 32, Iss. 1, pp. 4-24
Open Access | Times Cited: 3364
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Jeong Joon Park, Pete Florence, Julian Straub, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019), pp. 165-174
Closed Access | Times Cited: 2690
KPConv: Flexible and Deformable Convolution for Point Clouds
Hugues Thomas, Charles R. Qi, Jean‐Emmanuel Deschaud, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019), pp. 6410-6419
Open Access | Times Cited: 2258
SuperGlue: Learning Feature Matching With Graph Neural Networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 4937-4946
Open Access | Times Cited: 1789
Deep Learning for 3D Point Clouds: A Survey
Yulan Guo, Hanyun Wang, Qingyong Hu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020) Vol. 43, Iss. 12, pp. 4338-4364
Open Access | Times Cited: 1630
PointConv: Deep Convolutional Networks on 3D Point Clouds
Wenxuan Wu, Zhongang Qi, Fuxin Li
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019), pp. 9613-9622
Open Access | Times Cited: 1617
Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey
Longlong Jing, Yingli Tian
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020) Vol. 43, Iss. 11, pp. 4037-4058
Open Access | Times Cited: 1614
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
Qingyong Hu, Bo Yang, Linhai Xie, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)
Open Access | Times Cited: 1523
PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
Shaoshuai Shi, Chaoxu Guo, Li Jiang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 10526-10535
Open Access | Times Cited: 1491
PCT: Point cloud transformer
Meng-Hao Guo, Jun-Xiong Cai, Zheng-Ning Liu, et al.
Computational Visual Media (2021) Vol. 7, Iss. 2, pp. 187-199
Open Access | Times Cited: 1317
A survey on deep learning techniques for image and video semantic segmentation
Alberto García-García, Sergio Orts‐Escolano, Sergiu Oprea, et al.
Applied Soft Computing (2018) Vol. 70, pp. 41-65
Closed Access | Times Cited: 1314
Point Transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Closed Access | Times Cited: 1248
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou, Ganqu Cui, Shengding Hu, et al.
arXiv (Cornell University) (2018)
Open Access | Times Cited: 1160
Graph convolutional networks: a comprehensive review
Si Zhang, Hanghang Tong, Jiejun Xu, et al.
Computational Social Networks (2019) Vol. 6, Iss. 1
Open Access | Times Cited: 1149
DeepGCNs: Can GCNs Go As Deep As CNNs?
Guohao Li, Matthias Müller, Ali Thabet, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019)
Open Access | Times Cited: 1113
Deep Hough Voting for 3D Object Detection in Point Clouds
Charles R. Qi, Or Litany, Kaiming He, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019), pp. 9276-9285
Open Access | Times Cited: 1046
Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks
Christopher Morris, Martin Ritzert, Matthias Fey, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2019) Vol. 33, Iss. 01, pp. 4602-4609
Open Access | Times Cited: 1003
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey, Jan Eric Lenssen
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 951
Relation-Shape Convolutional Neural Network for Point Cloud Analysis
Yongcheng Liu, Bin Fan, Shiming Xiang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019), pp. 8887-8896
Closed Access | Times Cited: 862
Deep Closest Point: Learning Representations for Point Cloud Registration
Yue Wang, Justin Solomon
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019), pp. 3522-3531
Open Access | Times Cited: 811
PCN: Point Completion Network
Wentao Yuan, Tejas Khot, David Held, et al.
2021 International Conference on 3D Vision (3DV) (2018), pp. 728-737
Open Access | Times Cited: 747
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
Weijing Shi, Raj Rajkumar
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 1708-1716
Open Access | Times Cited: 731
PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing
Hengshuang Zhao, Li Jiang, Chi‐Wing Fu, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
Closed Access | Times Cited: 729
PointNetLK: Robust & Efficient Point Cloud Registration Using PointNet
Yasuhiro Aoki, Hunter Goforth, Rangaprasad Arun Srivatsan, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019), pp. 7156-7165
Closed Access | Times Cited: 686
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