Awesome LiDAR Analysis

Baselines Implementations

Large Scale

CNN/MLP

Graph-based

Hierachical and other

Paper & Code Repo

Survey

Graph Neural Network/Deep Learning for Point Cloud

  1. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
    CVPR, 2017 (citation 2908)
    [Torch Geometric] [Torch Point 3D]
  2. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
    NIPS, 2017 (citation 1748)
    [Torch Geometric] [Torch Point 3D]
  3. Dynamic Graph CNN for Learning on Point Clouds
    ACM Transactions on Graphics 2019 (citation 681)
    [Torch Geometric]
  4. PointCNN: Convolution on x-transformed points
    NIPS 2018 (citation 323)
    [Torch Geometric][Torch Point 3D]
  5. Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
    CVPR 2017 (citation 361)
  6. RGCNN: Regularized Graph CNN for Point Cloud Segmentation
    ACM MM 2018 (citation 50)
  7. Grid-GCN for Fast and Scalable Point Cloud Learning
    CVPR 2020
  8. Graph Attention Convolution for Point Cloud Semantic Segmentation
    CVPR 2019 (citation 36)
  9. Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
    (citation 235)
  10. Relation-Shape Convolutional Neural Network for Point Cloud Analysis [arXiv] [CVF]
    CVPR 2019 (citation 80)
    [Official Code][Torch Point 3D]
  11. Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
    CVPR 2020
  12. LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention
    CVPR 2020
  13. KPConv: Flexible and Deformable Convolution for Point Clouds
    ICCV 2019 (citation 130)
    [Torch Point 3D]

Sampling

  1. https://arxiv.org/abs/1912.03663(CVPR 2020)
  2. https://arxiv.org/abs/1904.03375(CVPR 2019 citation:37)
  3. https://openaccess.thecvf.com/content_CVPRW_2019/papers/UG2+%20Prize%20Challenge/Arief_Density-Adaptive_Sampling_for_Heterogeneous_Point_Cloud_Object_Segmentation_in_Autonomous_CVPRW_2019_paper.pdf(CVPR 2019 citation:2)
  4. https://arxiv.org/abs/1806.01759(citation: 79)
  5. https://pdfs.semanticscholar.org/1ef2/549c6a0bb6fbe9bd39af8f2913ce53e02817.pd
  6. https://arxiv.org/abs/1911.11236 (CVPR2019 citation:51)

TBD

Generation

test section

Method Task Place holder Implementation
Dynamic Graph CNN classification, segmentation Tensorflow+Pytorch
GACNet classification, segmentation Tensorflow Pytorch
Superpoint Graphs classification Pytorch
PointCNN classification, segmentation Tensorflow Pytorch_geometric