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Summary: Set up landing page, docs page, and html versions of the ipython notebook tutorials. Pull Request resolved: https://github.com/fairinternal/pytorch3d/pull/11 Reviewed By: gkioxari Differential Revision: D19730380 Pulled By: nikhilaravi fbshipit-source-id: 5df8d3f2ac2f8dce4d51f5d14fc336508c2fd0ea
14 lines
889 B
Markdown
14 lines
889 B
Markdown
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sidebar_label: Why PyTorch3d
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---
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# Why PyTorch3d
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Our goal with PyTorch3D is to help accelerate research at the intersection of deep learning and 3D. 3D data is more complex than 2D images and while working on projects such as [Mesh R-CNN](https://github.com/facebookresearch/meshrcnn) and [C3DPO](https://github.com/facebookresearch/c3dpo_nrsfm), we encountered several challenges including 3D data representation, batching, and speed. We have developed many useful operators and abstractions for working on 3D deep learning and want to share this with the community to drive novel research in this area.
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In PyTorch3D we have included efficient 3D operators, heterogeneous batching capabilities, and a modular differentiable rendering API, to equip researchers in this field with a much needed toolkit to implement cutting-edge research with complex 3D inputs.
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