diff --git a/README.md b/README.md
index 7ce02b0..9a2c20d 100644
--- a/README.md
+++ b/README.md
@@ -217,6 +217,13 @@ Speed is measured with `inference_speed_test.py` for reference.
* Note 2: GPUs before Turing architecture does not support FP16 inference, so GTX 1080 Ti uses FP32.
* Note 3: We only measure tensor throughput. The provided video conversion script in this repo is expected to be much slower, because it does not utilize hardware video encoding/decoding and does not have the tensor transfer done on parallel threads. If you are interested in implementing hardware video encoding/decoding in Python, please refer to [PyNvCodec](https://github.com/NVIDIA/VideoProcessingFramework).
+
+
+## Third-party Resources
+
+* NCNN C++ and Android Demo: [ncnn_Android_RobustVideoMatting](https://github.com/FeiGeChuanShu/ncnn_Android_RobustVideoMatting) from [FeiGeChuanShu](https://github.com/FeiGeChuanShu)
+* ONNXRuntime C++ Demo: [lite.ai.toolkit](https://github.com/DefTruth/lite.ai.toolkit/blob/main/ort/cv/rvm.cpp) and [demo](https://github.com/DefTruth/RobustVideoMatting.lite.ai.toolkit) from [DefTruth](https://github.com/DefTruth)
+
## Project Members
diff --git a/README_zh_Hans.md b/README_zh_Hans.md
index 5f797a9..61f2dce 100644
--- a/README_zh_Hans.md
+++ b/README_zh_Hans.md
@@ -216,7 +216,13 @@ convert_video = torch.hub.load("PeterL1n/RobustVideoMatting", "converter")
* 注释2:图灵架构之前的 GPU 不支持 FP16 推理,所以 GTX 1080 Ti 使用 FP32。
* 注释3:我们只测量张量吞吐量(tensor throughput)。 提供的视频转换脚本会慢得多,因为它不使用硬件视频编码/解码,也没有在并行线程上完成张量传输。如果您有兴趣在 Python 中实现硬件视频编码/解码,请参考 [PyNvCodec](https://github.com/NVIDIA/VideoProcessingFramework)。
-
+
+
+## 第三方资源
+
+* NCNN C++ and Android Demo: [ncnn_Android_RobustVideoMatting](https://github.com/FeiGeChuanShu/ncnn_Android_RobustVideoMatting) from [FeiGeChuanShu](https://github.com/FeiGeChuanShu)
+* ONNXRuntime C++ Demo: [lite.ai.toolkit](https://github.com/DefTruth/lite.ai.toolkit/blob/main/ort/cv/rvm.cpp) and [demo](https://github.com/DefTruth/RobustVideoMatting.lite.ai.toolkit) from [DefTruth](https://github.com/DefTruth)
+
## 项目成员
* [Shanchuan Lin](https://www.linkedin.com/in/shanchuanlin/)