diff --git a/README.md b/README.md
index 1b9f4b9..0d6cd28 100644
--- a/README.md
+++ b/README.md
@@ -25,8 +25,8 @@ Light Gaussian implementation: [This link](https://github.com/pablodawson/4DGaus
 
 
 ## News
-
-2024.02: Accepted by CVPR 2024. We delete some logging settings for debugging, the corrected training time is only **8 mins** (20 mins before) in D-NeRF datasets and **30 mins** (1 hour before) in HyperNeRF datasets. The rendering quality is not affected.
+2024.02.28: Update SIBR viewer guidance.
+2024.02.27: Accepted by CVPR 2024. We delete some logging settings for debugging, the corrected training time is only **8 mins** (20 mins before) in D-NeRF datasets and **30 mins** (1 hour before) in HyperNeRF datasets. The rendering quality is not affected.
 
 ## Environmental Setups
 
@@ -133,7 +133,8 @@ cp -r data/your-ns-data/images data/your-ns-data/colmap/images
 python train.py -s data/your-ns-data/colmap --port 6017 --expname "custom" --configs arguments/hypernerf/default.py 
 
 ```
-
+## Viewer
+[Watch me](./docs/viewer_usage.md)
 ## Scripts
 
 There are some helpful scripts in , please feel free to use them.
diff --git a/assets/port_forward.png b/assets/port_forward.png
new file mode 100644
index 0000000..a4d9917
Binary files /dev/null and b/assets/port_forward.png differ
diff --git a/assets/viewer.mp4 b/assets/viewer.mp4
new file mode 100644
index 0000000..13006e6
Binary files /dev/null and b/assets/viewer.mp4 differ
diff --git a/docs/viewer_usage.md b/docs/viewer_usage.md
new file mode 100644
index 0000000..faad91d
--- /dev/null
+++ b/docs/viewer_usage.md
@@ -0,0 +1,35 @@
+# 4D Gaussian Splatting
+The viewer is downloads from [3D-GS](https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/binaries/viewers.zip), you can extract the zip file under the folder of 4D-GS like:
+```
+├── 4DGaussians
+|   |viewers
+|      ├── bin
+|      ├── resources
+|      ├── shaders
+|      |...
+|   | train.py
+|   | test.py
+|   | ...(other files)
+```
+## How to use viewer?
+If you train the 4D-GS on locally:
+```python
+./viewers/bin/SIBR_remoteGaussian_app.exe --port 6017 # port should be same with your trainging code.
+```
+If you train the 4D-GS on the server, you should add a port forward, in VSCode, like this:
+![port_forward](../assets/port_forward.png)
+Then you could clone this repo on your personal computer, and download a D-NeRF dataset, like this:
+```
+├── 4DGaussians
+|   |viewers
+|      ├── bin
+|      ├── resources
+|      ├── shaders
+|      |...
+│   | data 
+│     ├── dnerf
+|   | train.py
+|   | test.py
+|   | ...(other files)
+```
+And the rendering speed may mainly depends on your network bandwidth.
diff --git a/submodules/depth-diff-gaussian-rasterization b/submodules/depth-diff-gaussian-rasterization
index f2d8fa9..e495066 160000
--- a/submodules/depth-diff-gaussian-rasterization
+++ b/submodules/depth-diff-gaussian-rasterization
@@ -1 +1 @@
-Subproject commit f2d8fa9921ea9a6cb9ac1c33a34ebd1b11510657
+Subproject commit e49506654e8e11ed8a62d22bcb693e943fdecacf
diff --git a/train.py b/train.py
index 4080482..2d3b2f9 100644
--- a/train.py
+++ b/train.py
@@ -403,8 +403,8 @@ if __name__ == "__main__":
     parser.add_argument('--port', type=int, default=6009)
     parser.add_argument('--debug_from', type=int, default=-1)
     parser.add_argument('--detect_anomaly', action='store_true', default=False)
-    parser.add_argument("--test_iterations", nargs="+", type=int, default=[3000,14000,20000])
-    parser.add_argument("--save_iterations", nargs="+", type=int, default=[3000,14000,20000, 30_000, 45000, 60000])
+    parser.add_argument("--test_iterations", nargs="+", type=int, default=[3000,7000,14000])
+    parser.add_argument("--save_iterations", nargs="+", type=int, default=[ 14000, 20000, 30_000, 45000, 60000])
     parser.add_argument("--quiet", action="store_true")
     parser.add_argument("--checkpoint_iterations", nargs="+", type=int, default=[])
     parser.add_argument("--start_checkpoint", type=str, default = None)