# pcrnet

**Repository Path**: lewhy2004/pcrnet

## Basic Information

- **Project Name**: pcrnet
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-19
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# PCRNet: Point Cloud Registration Network using PointNet Encoding

Source Code Author: Vinit Sarode and Xueqian Li

**[Paper](https://arxiv.org/abs/1908.07906) | 
[Website](https://vinitsarode.weebly.com/pcrnet.html) |
[Video](https://youtu.be/zPUHZYUwPJA) | 
[Pytorch Implementation](https://github.com/vinits5/pcrnet_pytorch)**

<p align="center">
	<img src="https://github.com/vinits5/pcrnet/blob/master/images/first_fig.png" height="300">
</p>

### Requirements:
1. Cuda 10
2. tensorflow==1.14
3. transforms3d==0.3.1
4. h5py==2.9.0

### Dataset:
Path for dataset: [Link](https://drive.google.com/drive/folders/19X68JeiXdeZgFp3cuCVpac4aLLw4StHZ?usp=sharing)
1. Download 'train_data' folder from above link for iterative PCRNet.
2. Download 'car_data' folder from above link for PCRNet.

### Pretrained Model:
Download pretrained models from [Link](https://drive.google.com/drive/folders/1o3F6677n6FVuMArNVWTyP5Hn3m856eEG?usp=sharing)

### How to use code:

#### Compile loss functions:
1. cd utils/pc_distance
2. make -f makefile_10.0 clean
3. make -f makefile_10.0

#### Train Iterative-PCRNet:
1. chmod +x train_itrPCRNet.sh
2. ./train_itrPCRNet.sh

#### Train PCRNet:
1. chmod +x train_PCRNet.sh
2. ./train_PCRNet.sh

### Citation

```
@InProceedings{vsarode2019pcrnet,
       author = {Sarode, Vinit and Li, Xueqian and Goforth, Hunter and Aoki, Yasuhiro and Arun Srivatsan, Rangaprasad and Lucey, Simon and Choset, Howie},
       title = {PCRNet: Point Cloud Registration Network using PointNet Encoding},
       month = {Aug},
       year = {2019}
}
```