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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

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arxiv link: https://arxiv.org/abs/1612.00593 Deep Learning on 3D Classification and Segmentation

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Introduction Introduction
Introduction
Introduction
Related Work Introduction
Introduction
Problem Statement Introduction
Introduction
Deep learning on Point sets Deep learning on Point Sets
Deep learning on Point Sets – Properties of pointsets Our input is a subset of points from an Euclidean space 3 main properties • Unordered → Permutation invariance • Invariance under transformations • Interaction among points 2D array representation N D
Deep learning on Point Sets – PointNet Architecture
1. the max pooling layer as a symmetric function to aggregate information from all the points 2. a local and global information combination structure 3. two joint alignment networks that align both input points and point features. 3 key modules Deep learning on Point Sets – PointNet Architecture
1. the max pooling layer as a symmetric function to aggregate information from all the points Unordered input RNN training Symmetric function Deep learning on Point Sets – PointNet Architecture Permutation invariance
1. the max pooling layer as a symmetric function to aggregate information from all the points Deep learning on Point Sets – PointNet Architecture
Deep learning on Point Sets – PointNet Architecture 1. the max pooling layer as a symmetric function to aggregate information from all the points – Q: What symmetric functions can be constructed by PointNet? 시멘코 정리?
Deep learning on Point Sets – PointNet Architecture
2. a local and global information combination structure Deep learning on Point Sets – PointNet Architecture
3. two joint alignment networks that align both input points and point features. Deep learning on Point Sets – PointNet Architecture
3. two joint alignment networks that align both input points and point features. Deep learning on Point Sets – PointNet Architecture
3. two joint alignment networks that align both input points and point features. Deep learning on Point Sets – PointNet Architecture STN
Result Deep learning on Point Sets
Deep learning on Point Sets
Deep learning on Point Sets Robustness to data corruption
Deep learning on Point Sets Visualizing PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

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PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

  • 1.
  • 9. Deep learning on Point sets Deep learning on Point Sets
  • 10. Deep learning on Point Sets – Properties of pointsets Our input is a subset of points from an Euclidean space 3 main properties • Unordered → Permutation invariance • Invariance under transformations • Interaction among points 2D array representation N D
  • 11. Deep learning on Point Sets – PointNet Architecture
  • 12. 1. the max pooling layer as a symmetric function to aggregate information from all the points 2. a local and global information combination structure 3. two joint alignment networks that align both input points and point features. 3 key modules Deep learning on Point Sets – PointNet Architecture
  • 13. 1. the max pooling layer as a symmetric function to aggregate information from all the points Unordered input RNN training Symmetric function Deep learning on Point Sets – PointNet Architecture Permutation invariance
  • 14. 1. the max pooling layer as a symmetric function to aggregate information from all the points Deep learning on Point Sets – PointNet Architecture
  • 15. Deep learning on Point Sets – PointNet Architecture 1. the max pooling layer as a symmetric function to aggregate information from all the points – Q: What symmetric functions can be constructed by PointNet? 시멘코 정리?
  • 16. Deep learning on Point Sets – PointNet Architecture
  • 17. 2. a local and global information combination structure Deep learning on Point Sets – PointNet Architecture
  • 18. 3. two joint alignment networks that align both input points and point features. Deep learning on Point Sets – PointNet Architecture
  • 19. 3. two joint alignment networks that align both input points and point features. Deep learning on Point Sets – PointNet Architecture
  • 20. 3. two joint alignment networks that align both input points and point features. Deep learning on Point Sets – PointNet Architecture STN
  • 22. Deep learning on Point Sets
  • 23. Deep learning on Point Sets Robustness to data corruption
  • 24. Deep learning on Point Sets Visualizing PointNet