ODFNet: Using orientation distribution functions to characterize 3D point clouds

Author:

Sahin Yusuf H.ORCID,Mertan AlicanORCID,Unal GozdeORCID

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Human-Computer Interaction,General Engineering

Reference63 articles.

1. Deep learning;LeCun;Nature,2015

2. Qi CR, Su H, Mo K, Guibas LJ. Pointnet: Deep learning on point sets for 3d classification and segmentation, In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017. p. 652–660.

3. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;Qi,2017

4. Deng H, Birdal T, Ilic S. Ppfnet: Global context aware local features for robust 3d point matching, In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018. p. 195–205.

5. Xu Y, Fan T, Xu M, Zeng L, Qiao Y. Spidercnn: Deep learning on point sets with parameterized convolutional filters, In: Proceedings of the European Conference on Computer Vision (ECCV), 2018. p. 87–102.

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