Uploaded June 2020 | Updated September 2026, 1 day ago
Learn more about how it works in this video by PyTorch3D co-creator and software engineer Nikhila Ravi: ai.facebook.com/blog/-introducing-pytorch3d-an-open-source-library-for-3d-deep-learning
In the same way that Torchvision and Detectron2 offer highly optimized libraries for 2D computer vision, PyTorch3D offers capabilities that support 3D data. Our open source library for 3D deep learning includes support for easy batching of heterogeneous meshes and point clouds, optimized implementations of common 3D operators such as Chamfer Loss and Graph Conv, as well as a modular, differentiable renderer for point clouds and meshes. We’re already using PyTorch3D at Facebook for research projects such as Mesh R-CNN and SynSin.
Learn more about how it works in this video by PyTorch3D co-creator and software engineer Nikhila Ravi: ai.facebook.com/blog/-introducing-pytorch3d-an-open-source-library-for-3d-deep-learning
In the same way that Torchvision and Detectron2 offer highly optimized libraries for 2D computer vision, PyTorch3D offers capabilities that support 3D data. Our open source library for 3D deep learning includes support for easy batching of heterogeneous meshes and point clouds, optimized implementations of common 3D operators such as Chamfer Loss and Graph Conv, as well as a modular, differentiable renderer for point clouds and meshes. We’re already using PyTorch3D at Facebook for research projects such as Mesh R-CNN and SynSin.
