diff --git a/README.md b/README.md
index 2a7629729..fe22efc91 100644
--- a/README.md
+++ b/README.md
@@ -134,3 +134,8 @@ CC=clang CXX=clang++ CFLAGS='-stdlib=libc++' MMCV_WITH_OPS=1 pip install -e .
 Note: If you would like to use `opencv-python-headless` instead of `opencv-python`,
 e.g., in a minimum container environment or servers without GUI,
 you can first install it before installing MMCV to skip the installation of `opencv-python`.
+
+
+### TroubleShooting
+
+If you meet issues when running or compiling mmcv, we list some common issues in [TROUBLESHOOTING.md](docs/trouble_shooting.md).
diff --git a/docs/index.rst b/docs/index.rst
index 0fd8dbb33..c7ef3936d 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -15,6 +15,7 @@ Contents
    runner.md
    cnn.md
    ops.md
+   trouble_shooting.md
    api.rst
 
 
diff --git a/docs/trouble_shooting.md b/docs/trouble_shooting.md
new file mode 100644
index 000000000..928027540
--- /dev/null
+++ b/docs/trouble_shooting.md
@@ -0,0 +1,37 @@
+## Trouble Shooting
+
+We list some common troubles faced by many users and their corresponding solutions here.
+Feel free to enrich the list if you find any frequent issues and have ways to help others to solve them.
+
+- Compatibility issue between MMCV and MMDetection; "ConvWS is already registered in conv layer"
+
+    Please install the correct version of MMCV for the version of your MMDetection following the instruction above.
+
+- "No module named 'mmcv.ops'"; "No module named 'mmcv._ext'".
+
+    1. Uninstall existing mmcv in the environment using `pip uninstall mmcv`.
+    2. Install mmcv-full following the instruction above.
+
+- "invalid device function" or "no kernel image is available for execution".
+
+    1. Check the CUDA compute capability of you GPU.
+    2. Run `python mmdet/utils/collect_env.py` to check whether PyTorch, torchvision,
+       and MMCV are built for the correct GPU architecture.
+       You may need to set `TORCH_CUDA_ARCH_LIST` to reinstall MMCV.
+       The compatibility issue could happen when  using old GPUS, e.g., Tesla K80 (3.7) on colab.
+    3. Check whether the running environment is the same as that when mmcv/mmdet is compiled.
+       For example, you may compile mmcv using CUDA 10.0 bug run it on CUDA9.0   environments.
+
+- "undefined symbol" or "cannot open xxx.so".
+
+    1. If those symbols are CUDA/C++ symbols (e.g., libcudart.so or GLIBCXX), check
+       whether the CUDA/GCC runtimes are the same as those used for compiling mmcv.
+    2. If those symbols are Pytorch symbols (e.g., symbols containing caffe, aten, and TH), check whether
+       the Pytorch version is the same as that used for compiling mmcv.
+    3. Run `python mmdet/utils/collect_env.py` to check whether PyTorch, torchvision,
+       and MMCV are built by and running on the same environment.
+
+- "RuntimeError: CUDA error: invalid configuration argument".
+
+    This error may be due to your poor GPU. Try to decrease the value of [THREADS_PER_BLOCK](https://github.com/open-mmlab/mmcv/blob/cac22f8cf5a904477e3b5461b1cc36856c2793da/mmcv/ops/csrc/common_cuda_helper.hpp#L10)
+    and recompile mmcv.