Point Cloud Classification Using Deep Learning and Classical Machine Learning Methods

Supported models are available under config/config.yaml.

Usage

• Dependencies

  conda env create -f environment.yml
  

• Usage
  • Train

    python trainer.py --model DGCNNC --train
    

  • Evaluation

    python trainer.py --model DGCNNC 
    

Adding your own model

ToDo

Training on H-BRS cluster

Acknowledgement

• PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
• PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
• Dynamic Graph CNN for Learning on Point Clouds
• 3DmFV : Three-Dimensional Point Cloud Classification in Real-Time using Convolutional Neural Networks
• PointCNN: Convolution On X-Transformed Points
• SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters