implicitron readme updates

Summary: add link in main readme

Reviewed By: kjchalup

Differential Revision: D38560053

fbshipit-source-id: 0814febb67d0580394cfa2664e49e31ff7254bd4
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Jeremy Reizenstein 2022-08-09 20:48:51 -07:00 committed by Facebook GitHub Bot
parent af48430ec0
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2 changed files with 3 additions and 1 deletions

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@ -12,6 +12,7 @@ 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
- Implicitron, see [its README](projects/implicitron_trainer), a framework for new-view synthesis via implicit representations.
PyTorch3D is designed to integrate smoothly with deep learning methods for predicting and manipulating 3D data.
For this reason, all operators in PyTorch3D:
@ -93,6 +94,7 @@ In alphabetical order:
* Amitav Baruah
* Steve Branson
* Krzysztof Chalupka
* Luya Gao
* Georgia Gkioxari
* Taylor Gordon

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@ -37,7 +37,7 @@ See [Running](#running) section below for examples of training and evaluation co
To plug in custom implementations, for example, of renderer or implicit-function protocols, you need to create your own runner script and import the plug-in implementations there.
First, install PyTorch3D and Implicitron dependencies as described in the previous section.
Then, implement the custom script; copying `pytorch3d/projects/implicitron_trainer/experiment.py` is a good place to start.
Then, implement the custom script; copying `pytorch3d/projects/implicitron_trainer` is a good place to start.
See [Custom plugins](#custom-plugins) for more information on how to import implementations and enable them in the configs.