NVIDIA Kaolin Library is a suite of tools designed to accelerate 3D deep learning research. It provides a PyTorch API for working with various 3D representations and includes a growing collection of GPU-optimized operations such as modular differentiable rendering, fast conversions between representations, data loading, camera classes, volumetric acceleration data structures, 3D checkpoints, and more.

Features

• Modular Differentiable Rendering: Develop cutting-edge inverse graphics applications using optimized implementations of differentiable rendering.
• Representation Agnostic Physics Simulation: Versatile framework for reduced elastic simulations of 3D objects in any geometric representation.
• Continuous Additions: Regular updates with new research components from NVIDIA Toronto AI Lab and across NVIDIA.
• USD Integration in Omniverse: Connect 3D research to USD content on a live USD stage rendered in NVIDIA Omniverse.
• Consistent 3D Data Loading: Load USD, OBJ, and glTF 3D formats into a consistent PyTorch representation.
• GPU-Optimized 3D Operations: Fast and reliable conversion operations, including point cloud sampling, topology processing, and sparse convolutions.

Benefits

• Efficiency: Accelerates 3D deep learning research with GPU-optimized operations.
• Flexibility: Supports various 3D representations and geometric processing.
• Integration: Seamlessly integrates with NVIDIA Omniverse and other AI frameworks.
• Scalability: Suitable for large-scale 3D datasets and simulations.
• User-Friendly: Provides intuitive tools and APIs for 3D deep learning research.