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path invariance map network research project
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LICENSE
README.md
cmd
intro.JPG
ops.py
pc_util.py
pointnet2_sem_seg.py
pointnet2_sem_seg_voxel.py
pointnet_util.py
provider.py
result.JPG
scannet_dataset.py
scannet_dataset_multi.py
scene_util.py
suncg_dataset_multi.py
tf_util.py
train_pc_joint_multi_combinesample_queue.py
train_voxel_joint_multi_v1.py
train_voxel_joint_multi_v2.py

README.md

Path Invariance Network in Tensorflow

Tensorflow implementation of one application in Path Invariance Map Networks: 3D 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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