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+<img src="https://github.com/facebookresearch/pytorch3d/blob/master/.github/pytorch3dlogo.png" width="900"/>
+
+[![CircleCI](https://circleci.com/gh/facebookresearch/pytorch3d.svg?style=svg)](https://circleci.com/gh/facebookresearch/pytorch3d)
+[![Anaconda-Server Badge](https://anaconda.org/pytorch3d/pytorch3d/badges/version.svg)](https://anaconda.org/pytorch3d/pytorch3d)
+
+# Introduction
+
+PyTorch3d provides efficient, reusable components for 3D Computer Vision research with [PyTorch](https://pytorch.org).
+
+Key features include:
+
+- Data structure for storing and manipulating triangle meshes
+- Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions)
+- A differentiable mesh renderer
+
+PyTorch3d is designed to integrate smoothly with deep learning methods for predicting and manipulating 3D data.
+For this reason, all operators in PyTorch3d:
+
+- Are implemented using PyTorch tensors
+- Can handle minibatches of hetereogenous data
+- Can be differentiated
+- Can utilize GPUs for acceleration
+
+Within FAIR, PyTorch3d has been used to power research projects such as [Mesh R-CNN](https://arxiv.org/abs/1906.02739).
+
+## Installation
+
+For detailed instructions refer to [INSTALL.md](INSTALL.md).
+
+## License
+
+PyTorch3d is released under the [BSD-3-Clause License](LICENSE).
+
+## Tutorials
+
+Get started with PyTorch3d by trying one of the tutorial notebooks.
+
+|<img src="https://github.com/facebookresearch/pytorch3d/blob/master/.github/dolphin_deform.gif" width="310"/>|<img src="https://github.com/facebookresearch/pytorch3d/blob/master/.github/bundle_adjust.gif" width="310"/>|
+|:-----------------------------------------------------------------------------------------------------------:|:--------------------------------------------------:|
+| [Deform a sphere mesh to dolphin](https://github.com/fairinternal/pytorch3d/blob/master/docs/tutorials/deform_source_mesh_to_target_mesh.ipynb)| [Bundle adjustment](https://github.com/fairinternal/pytorch3d/blob/master/docs/tutorials/bundle_adjustment.ipynb) |
+
+| <img src="https://github.com/facebookresearch/pytorch3d/blob/master/.github/render_textured_mesh.gif" width="310"/> | <img src="https://github.com/facebookresearch/pytorch3d/blob/master/.github/camera_position_teapot.gif" width="310" height="310"/>
+|:------------------------------------------------------------:|:--------------------------------------------------:|
+| [Render textured meshes](https://github.com/fairinternal/pytorch3d/blob/master/docs/tutorials/render_textured_meshes.ipynb)| [Camera position optimization](https://github.com/fairinternal/pytorch3d/blob/master/docs/tutorials/camera_position_optimization_with_differentiable_rendering.ipynb)|
+
+## Documentation
+
+Learn more about the API by reading the PyTorch3d [documentation](https://pytorch3d.readthedocs.org/).
+
+We also have deep dive notes on several API components:
+
+- [Heterogeneous Batching](https://github.com/facebookresearch/pytorch3d/tree/master/docs/notes/batching.md)
+- [Mesh IO](https://github.com/facebookresearch/pytorch3d/tree/master/docs/notes/meshes_io.md)
+- [Differentiable Rendering](https://github.com/facebookresearch/pytorch3d/tree/master/docs/notes/renderer_getting_started.md)
+
+## Development
+
+We welcome new contributions to Pytorch3d and we will be actively maintaining this library! Please refer to [CONTRIBUTING.md](./.github/CONTRIBUTING.md) for full instructions on how to run the code, tests and linter, and submit your pull requests.
+
+
+## Contributors
+
+PyTorch3d is written and maintained by the Facebook AI Research Computer Vision Team.
+
+## Citation
+
+If you find PyTorch3d useful in your research, please cite:
+
+```bibtex
+@misc{ravi2020pytorch3d,
+  author =       {Nikhila Ravi and Jeremy Reizenstein and David Novotny and Taylor Gordon
+                  and Wan-Yen Lo and Justin Johnson and Georgia Gkioxari},
+  title =        {PyTorch3D},
+  howpublished = {\url{https://github.com/facebookresearch/pytorch3d}},
+  year =         {2020}
+}
+```