Implement a new model: Point-BERT 🌟
Author: AdonaiVera
Pull request: no
Labels: name: New model

### Model description

Hi, I’m Adonai vera; I’m looking to contribute with a new point cloud model; Point cloud has become very relevant in applications such as autonomous cars, inspections, architecture, reconstruction, and more. Segmentation algorithms allow us to extract valuable information from these types of files. That is why it is very important for me to contribute to the HF community with the architecture of a new Point-Bert model. Point-BERT is a Pre-training 3D Point Cloud Transformers with Masked Point Modeling. According to the state of the art, it is one of the best models, surpassing PointNet, Pointnet++, and Transformer-OcCo, among others.

**Short description of the model and link to the paper:**
They devise a Masked Point Modeling (MPM) task to pre-train point cloud Transformers. Specifically, they first divide a point cloud into several local point patches. A point cloud Tokenizer with a discrete Variational AutoEncoder (dVAE) is designed to generate discrete point tokens containing meaningful local information. Then, they randomly mask out some patches of input point clouds and feed them into the backbone Transformers. (Abstract)

[Link to the paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Yu_Point-BERT_Pre-Training_3D_Point_Cloud_Transformers_With_Masked_Point_Modeling_CVPR_2022_paper.pdf)

**Link to the implementation if it is open-source:**

[Pre-trained model in github](https://github.com/lulutang0608/Point-BERT)

 [Talk about the new arquicture in CVPR 2022](https://www.youtube.com/watch?v=KMOCw68Veoo)

**Link to the model weights if they are available:**

[Cfgs](https://github.com/lulutang0608/Point-BERT/tree/master/cfgs)

[Architecture](https://github.com/lulutang0608/Point-BERT/blob/master/models/Point_BERT.py)

I’m happy to contribute to this process, but it's important to know If this model can be valuable to the community.

PDT: I'm trying to connect with the model's authors to get more insights into the implementation. 🤗 
[EDIT] I talked with Xumin, one of the model's authors, and they support all the deployment in HF. 🚀🚀🚀

The authors are: :woman_teacher: :man_teacher:
@lulutang0608
@yuxumin
@raoyongming


### Open source status

- [X] The model implementation is available
- [X] The model weights are available

### Provide useful links for the implementation
[Architecture](https://github.com/lulutang0608/Point-BERT/blob/master/models/Point_BERT.py)
[Cfgs](https://github.com/lulutang0608/Point-BERT/tree/master/cfgs)
[Talk about the new arquicture in CVPR 2022](https://www.youtube.com/watch?v=KMOCw68Veoo)
[Pre-trained model in github](https://github.com/lulutang0608/Point-BERT)
[Link to the paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Yu_Point-BERT_Pre-Training_3D_Point_Cloud_Transformers_With_Masked_Point_Modeling_CVPR_2022_paper.pdf)


Comments:
Hey @AdonaiVera, exciting! Pinging @NielsRogge, our expert in model contribution :smiley: exciting to see point cloud models!

Sure, let me know if you need any help :)

@AdonaiVera @NielsRogge Are there any updates on this model?