https://github.com/interdigitalinc/wrappingnet

Implementation of the WrappingNet
https://github.com/interdigitalinc/wrappingnet

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Implementation of the WrappingNet

• Host: GitHub
• URL: https://github.com/interdigitalinc/wrappingnet
• Owner: InterDigitalInc
• License: other
• Created: 2024-06-14T18:19:13.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-06-28T00:20:57.000Z (7 months ago)
• Last Synced: 2024-06-28T01:54:50.541Z (7 months ago)
• Language: Python
• Homepage:
• Size: 721 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# WrappingNet

Implementation of the WrappingNet architecture.


The entire framework is illustrated below.



## Data Preparation

The dataset for WrappingNet should be prepared as follows:

### For training

1. `mkdir -p datasets/Manifold40; cd datasets/Manifold40`

2. Download processed.zip from `https://aspera.pub/3O5IeFo` then move into `datasets/Manifold40/`

3. `unzip processed.zip`, then check the data under `datasets/Manifold40/processed/`

### For evaluation

4. `wget https://cg.cs.tsinghua.edu.cn/dataset/subdivnet/datasets/Manifold40.zip`

5. `unzip Manifold40.zip`

6. `mv Manifold40 raw` then check the data under `datasets/Manifold40/raw/`

## Dependencies

```

   pytorch

   pytorch-geometric

   pytorch-lightning

   pytorch-scatter

   botorch

   open3d

   numpy

```

## To Run

To use our generalized face convolutions, follow these steps:

1. Create a python environment with the above dependencies installed

2. Go to `./nndistance/` and run `python build.py install`. This will build the faster chamfer distance module.

3. Run `CUDA_VISIBLE_DEVICES={GPU}, bash scripts/LC.sh` or `CUDA_VISIBLE_DEVICES={GPU}, bash scripts/basesup3.sh` to launch a training script.

## Citation

Eric Lei, Muhammad Asad Lodhi, Jiahao Pang, Junghyun Ahn, Dong Tian, 


"*WrappingNet: Mesh Autoencoder via Deep Sphere Deformation*", 


To Appear in 2024 IEEE International Conference on Image Processing (ICIP).