Point Clouds

Papers

Learning on point cloud inputs

  1. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation – Qi et al. (CVPR 2017 – Oral)

  2. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space – Qi et al. (NIPS 2017)

  3. PointCNN – Li et al. (Arxiv 2018)
  4. Frustum PointNets for 3D Object Detection from RGB-D Data – Qi et al. (CVPR 2018)

  5. PU-Net: Point Cloud Upsampling Network – Yu et al. (CVPR 2018)

  6. PPFNet: Global Context Aware Local Features for Robust 3D Point Matching – Deng et al. (CVPR 2018)

  7. Dynamic Graph CNN for Learning on Point Clouds – Wang et al. (Arxiv 2018)

Point cloud generations

  1. PSGN: A Point Set Generation Network for 3D Object Reconstruction from a Single Image – Fan et al. (CVPR 2017 – Oral)
  2. DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image – Kurenkov et al. (WACV 2018)
  3. Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction – Lin et al. (AAAI 2018 – Oral)
  4. Learning Representations and Generative Models for 3D Point Clouds – Achlioptas et al. (ICLR-W 2017)
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