readme

README.md

@@ -42,6 +42,7 @@ The method demonstrates the first monocular SLAM solely based on 3D Gaussian Spl
 # Note
 - In an academic paper, please refer to our work as **Gaussian Splatting SLAM** or **MonoGS** for short (this repo's name) to avoid confusion with other works.
 - Differential Gaussian Rasteriser with camera pose gradient computation is available [here](https://github.com/rmurai0610/diff-gaussian-rasterization-w-pose.git).
+- **[New]** Speed-up version of our code is available in `dev.speedup` branch, It achieves up to 10fps on monocular fr3/office sequence while keeping consistent performance (tested on RTX4090/i9-12900K). The code will be merged into the main branch after further refactoring and testing.
 
 # Getting Started
 ## Installation
@@ -122,7 +123,7 @@ Connect the realsense camera to the PC on a **USB-3** port and then run:
 ```bash
 python slam.py --config configs/live/realsense.yaml
 ```
-We tested the method with [Intel Realsense d455](https://www.mouser.co.uk/new/intel/intel-realsense-depth-camera-d455/). We recommend using a similar global shutter camera for robust camera tracking. Please avoid aggressive camera motion, especially before the initial BA is performed. Check out [the first 15 seconds of our YouTube video](https://youtu.be/x604ghp9R_Q?si=S21HgeVTVfNe0BVL) to see how you should move the camera for initialisation.
+We tested the method with [Intel Realsense d455](https://www.mouser.co.uk/new/intel/intel-realsense-depth-camera-d455/). We recommend using a similar global shutter camera for robust camera tracking. Please avoid aggressive camera motion, especially before the initial BA is performed. Check out [the first 15 seconds of our YouTube video](https://youtu.be/x604ghp9R_Q?si=S21HgeVTVfNe0BVL) to see how you should move the camera for initialisation. We recommend to use the code in `dev.speed-up` branch for live demo.
 
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