diff --git a/INSTALL.md b/INSTALL.md
index 52b673fc..810b2c64 100644
--- a/INSTALL.md
+++ b/INSTALL.md
@@ -8,8 +8,8 @@
 The core library is written in PyTorch. Several components have underlying implementation in CUDA for improved performance. A subset of these components have CPU implementations in C++/PyTorch. It is advised to use PyTorch3D with GPU support in order to use all the features.
 
 - Linux or macOS or Windows
-- Python 3.6, 3.7, 3.8 or 3.9
-- PyTorch 1.8.0, 1.8.1, 1.9.0, 1.9.1, 1.10.0, 1.10.1, 1.10.2, 1.11.0 or 1.12.0.
+- Python 3.8, 3.9 or 3.10
+- PyTorch 1.9.0, 1.9.1, 1.10.0, 1.10.1, 1.10.2, 1.11.0, 1.12.0, 1.12.1 or 1.13.0.
 - torchvision that matches the PyTorch installation. You can install them together as explained at pytorch.org to make sure of this.
 - gcc & g++ ≥ 4.9
 - [fvcore](https://github.com/facebookresearch/fvcore)
@@ -21,11 +21,11 @@ The runtime dependencies can be installed by running:
 ```
 conda create -n pytorch3d python=3.9
 conda activate pytorch3d
-conda install -c pytorch pytorch=1.9.1 torchvision cudatoolkit=10.2
+conda install -c pytorch pytorch=1.9.1 torchvision cudatoolkit=11.6
 conda install -c fvcore -c iopath -c conda-forge fvcore iopath
 ```
 
-For the CUB build time dependency, if you are using conda, you can continue with
+For the CUB build time dependency, which you only need if you have CUDA older than 11.7, if you are using conda, you can continue with
 ```
 conda install -c bottler nvidiacub
 ```
@@ -78,14 +78,14 @@ Or, to install a nightly (non-official, alpha) build:
 conda install pytorch3d -c pytorch3d-nightly
 ```
 ### 2. Install from PyPI, on Mac only.
-This works with pytorch 1.12.0 only. The build is CPU only.
+This works with pytorch 1.13.0 only. The build is CPU only.
 ```
 pip install pytorch3d
 ```
 
 ### 3. Install wheels for Linux
 We have prebuilt wheels with CUDA for Linux for PyTorch 1.11.0, for each of the supported CUDA versions,
-for Python 3.7, 3.8 and 3.9. This is for ease of use on Google Colab.
+for Python 3.8 and 3.9. This is for ease of use on Google Colab.
 These are installed in a special way.
 For example, to install for Python 3.8, PyTorch 1.11.0 and CUDA 11.3
 ```
diff --git a/README.md b/README.md
index 27ab09c1..07e343c5 100644
--- a/README.md
+++ b/README.md
@@ -100,6 +100,7 @@ In alphabetical order:
 * Amitav Baruah
 * Steve Branson
 * Krzysztof Chalupka
+* Jiali Duan
 * Luya Gao
 * Georgia Gkioxari
 * Taylor Gordon
@@ -143,6 +144,8 @@ If you are using the pulsar backend for sphere-rendering (the `PulsarPointRender
 
 Please see below for a timeline of the codebase updates in reverse chronological order. We are sharing updates on the releases as well as research projects which are built with PyTorch3D. The changelogs for the releases are available under [`Releases`](https://github.com/facebookresearch/pytorch3d/releases),  and the builds can be installed using `conda` as per the instructions in [INSTALL.md](INSTALL.md).
 
+**[Oct 23rd 2022]:**   PyTorch3D [v0.7.1](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.7.1) released.
+
 **[Aug 10th 2022]:**   PyTorch3D [v0.7.0](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.7.0) released with Implicitron and MeshRasterizerOpenGL.
 
 **[Apr 28th 2022]:**   PyTorch3D [v0.6.2](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.6.2) released