Update!

README.md

@@ -77,13 +77,15 @@ If you find our work useful in your research, please consider citing:
 
 
 ### Updates
+* 01/03/2021: The SensatUrban has been accepted by CVPR 2021!
+* 11/02/2021: The dataset is available for download!
 * 07/09/2020: Initial release!
 
 
 ## Related Repos
-1. [RandLA-Net](https://github.com/QingyongHu/RandLA-Net) ![GitHub stars](https://img.shields.io/github/stars/QingyongHu/RandLA-Net.svg?style=flat&label=Star)
-2. [SoTA-Point-Cloud](https://github.com/QingyongHu/SoTA-Point-Cloud) ![GitHub stars](https://img.shields.io/github/stars/QingyongHu/SoTA-Point-Cloud.svg?style=flat&label=Star)
-3. [3D-BoNet](https://github.com/Yang7879/3D-BoNet) ![GitHub stars](https://img.shields.io/github/stars/Yang7879/3D-BoNet.svg?style=flat&label=Star)
-3. [SpinNet](https://github.com/QingyongHu/SpinNet) ![GitHub stars](https://img.shields.io/github/stars/QingyongHu/SpinNet.svg?style=flat&label=Star)
+1. [RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds](https://github.com/QingyongHu/RandLA-Net) ![GitHub stars](https://img.shields.io/github/stars/QingyongHu/RandLA-Net.svg?style=flat&label=Star)
+2. [SoTA-Point-Cloud: Deep Learning for 3D Point Clouds: A Survey](https://github.com/QingyongHu/SoTA-Point-Cloud) ![GitHub stars](https://img.shields.io/github/stars/QingyongHu/SoTA-Point-Cloud.svg?style=flat&label=Star)
+3. [3D-BoNet: Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds](https://github.com/Yang7879/3D-BoNet) ![GitHub stars](https://img.shields.io/github/stars/Yang7879/3D-BoNet.svg?style=flat&label=Star)
+3. [SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration](https://github.com/QingyongHu/SpinNet) ![GitHub stars](https://img.shields.io/github/stars/QingyongHu/SpinNet.svg?style=flat&label=Star)