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Path Invariance Network in Tensorflow

Tensorflow implementation of one application in Path Invariance Map Networks: 3D Scene Semantic Segmentation. Since we use pointnet2 codebase, some of the code are borrowed from there.

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Prerequisites

Usage

First, download dataset here. (Point clouds are collected by Pointnet++) The pre-trained models can be downloaded here. (Point clouds models are trained using Pointnet++, and voxel models are trained using 3D-U-Net. The training code for voxel models will be released soon.)

To train models with downloaded dataset:

$ ./cmd

All training commands are included in the cmd file. Testing results are logged during the training stage.

Results

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Author

Zaiwei Zhang

License

Our code is released under BSD License (see LICENSE file for details).

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path invariance map network research project

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