We present Kaolin, a PyTorch library aiming to accelerate 3D deep learning research. Kaolin provides efficient implementations of differentiable 3D modules for use in deep learning systems. With functionality to load and preprocess several popular 3D datasets, and native functions to manipulate meshes, pointclouds, signed distance functions, and voxel grids, Kaolin mitigates the need to write wasteful boilerplate code. Kaolin packages together several differentiable graphics modules including rendering, lighting, shading, and view warping. Kaolin also supports an array of loss functions and evaluation metrics for seamless evaluation and provides visualization functionality to render the 3D results. Importantly, we curate a comprehensive model zoo comprising many state-of-the-art 3D deep learning architectures, to serve as a starting point for future research endeavours. Kaolin is available as open-source software at https://github.com/NVIDIAGameWorks/kaolin/.

Kaolin是一个PyTorch库，旨在加速3D深度学习研究。它提供了不同iable 3D模块的有效实现，包括渲染、光照、阴影和视图变形，并提供了加载和预处理多个流行3D数据集的功能。同时，它支持多种损失函数和评估度量以及可视化功能。Kaolin也提供了一组包含许多最新的3D深度学习架构的综合模型动物园，成为未来研究的一个起点。

Kaolin：一个用于加速 3D 深度学习研究的 PyTorch 库