423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2025-08-02 03:42:50 +08:00
Code Issues Packages Projects Releases Wiki Activity

Update README with links to blog posts (#43)

Browse Source 
Summary: Pull Request resolved: https://github.com/fairinternal/pytorch3d/pull/43

Reviewed By: bottler

Differential Revision: D42791756

Pulled By: nikhilaravi

fbshipit-source-id: 498399c1ce30bb095579c4d66b6314a6aa846df3
This commit is contained in:
Nikhila Ravi 2023-01-27 01:57:54 -08:00 committed by Facebook GitHub Bot
parent 0b11a5dc6d
commit 7e750a3786
1 changed files with 3 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
README.md
View File

@ -12,7 +12,7 @@ Key features include:
- Data structure for storing and manipulating triangle meshes - Data structure for storing and manipulating triangle meshes
- Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions) - Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions)
- A differentiable mesh renderer - A differentiable mesh renderer
- Implicitron, see [its README](projects/implicitron_trainer), a framework for new-view synthesis via implicit representations. - Implicitron, see [its README](projects/implicitron_trainer), a framework for new-view synthesis via implicit representations. ([blog post](https://ai.facebook.com/blog/implicitron-a-new-modular-extensible-framework-for-neural-implicit-representations-in-pytorch3d/))
PyTorch3D is designed to integrate smoothly with deep learning methods for predicting and manipulating 3D data. PyTorch3D is designed to integrate smoothly with deep learning methods for predicting and manipulating 3D data.
For this reason, all operators in PyTorch3D: For this reason, all operators in PyTorch3D:
@ -24,6 +24,8 @@ For this reason, all operators in PyTorch3D:
Within FAIR, PyTorch3D has been used to power research projects such as [Mesh R-CNN](https://arxiv.org/abs/1906.02739). Within FAIR, PyTorch3D has been used to power research projects such as [Mesh R-CNN](https://arxiv.org/abs/1906.02739).
See our [blog post](https://ai.facebook.com/blog/-introducing-pytorch3d-an-open-source-library-for-3d-deep-learning/) to see more demos and learn about PyTorch3D.
## Installation ## Installation
For detailed instructions refer to [INSTALL.md](INSTALL.md). For detailed instructions refer to [INSTALL.md](INSTALL.md).