Update README.md

README.md

@@ -1,10 +1,27 @@
-## Mamba3D
+# Mamba3D 
+
+[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/mamba3d-enhancing-local-features-for-3d-point/supervised-only-3d-point-cloud-classification)](https://paperswithcode.com/sota/supervised-only-3d-point-cloud-classification?p=mamba3d-enhancing-local-features-for-3d-point)
+[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/mamba3d-enhancing-local-features-for-3d-point/3d-point-cloud-classification-on-modelnet40)](https://paperswithcode.com/sota/3d-point-cloud-classification-on-modelnet40?p=mamba3d-enhancing-local-features-for-3d-point)
+[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/mamba3d-enhancing-local-features-for-3d-point/3d-point-cloud-classification-on-scanobjectnn)](https://paperswithcode.com/sota/3d-point-cloud-classification-on-scanobjectnn?p=mamba3d-enhancing-local-features-for-3d-point)
+
+This repository contains the official implementation of the paper:
 
 [**[ACM MM 24] Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model**](https://arxiv.org/abs/2404.14966)
 
-### Code: https://github.com/xhanxu/Mamba3D
 
-### Pretrained weights:
+## 📰 News
+- [2024/8] We release the training and evaluation code! Pretrained weights are coming soon!
+- [2024/7] Our [MiniGPT-3D](https://github.com/tangyuan96/minigpt-3d) is also accepted by ACM MM24! We outperform existing large point-language models, using just about 1 day on 1 RTX 3090! Check it out!
+- [2024/7] Ours Mamba3D is accepted by ACM MM24!
+
+- [2024/4] We present Mamba3D, a state space model tailored for point cloud learning.
+<div style="text-align: center">
+<img src="media/mamba3d_total_v2.png" />
+</div>
+
+# 🥶 Code: https://github.com/xhanxu/Mamba3D
+
+## 🐟 Pretrained weights:
 
 You can find the pre-trained weights [here](./pretrain_pointmae/ckpt-last.pth).
 
@@ -17,8 +34,19 @@ Or, specifically as follows.
 | ScanObjectNN-hardest| no       | 91.81 | [ckpt](./scanobjectnn_hardest_scratch_91.81/ckpt-best-91.8.pth)    |
 | ScanObjectNN-hardest| Point-MAE | 92.05 | [ckpt](./scanobjectnn_hardest_pointmae_92.05/ckpt-best.pth)    |
 
-### If you have any questions or are looking for cooperation in related fields, please contact [Xu Han](https://xhanxu.github.io/) via xhanxu@hust.edu.cn. 
+## 😀 Contact
+If you have any questions or are looking for cooperation in related fields, please contact [Xu Han](https://xhanxu.github.io/) via xhanxu@hust.edu.cn. 
 
+## 📚 Citation
+If you find our work helpful, please consider citing:
+```bibtex
+@article{han2024mamba3d,
+  title={Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model},
+  author={Han, Xu and Tang, Yuan and Wang, Zhaoxuan and Li, Xianzhi},
+  journal={arXiv preprint arXiv:2404.14966},
+  year={2024}
+}
+```
 ---
 license: mit
 ---