Kaolin: A Library for 3D Intelligence

Has to be useful for building and testing 3D intelligence.

Kaolin: The first comprehensive library for 3-D deep learning research  by Ingrid Fadelli , Tech Xplore

As most real-world environments are three-dimensional, deep learning models designed to analyze videos or complete tasks in real-world environments should ideally be trained on 3-D data. Technological tools such as robots, self-driving vehicles, smartphones, and other devices are currently generating a growing amount of 3-D data that could eventually be processed by deep learning algorithms.

Up until now, however, training deep learning algorithms on this vast amount of 3-D data has been relatively difficult, as the necessary tools and platforms are only accessible to some artificial intelligence (AI) researchers. To address this lack of readily available tools, a team of researchers at NVIDIA has recently created Kaolin, a PyTorch open-source library aimed at advancing and facilitating 3-D deep learning research.

"Currently, there is not a single open-source software library that supports multiple representations of 3-D data, multiple tasks, and evaluation criteria," Krishna Murthy Jatavallabhula, one of the researchers who carried out the study, told TechXplore. "We decided to address this gap in the literature by creating Kaolin, the first comprehensive 3-D deep learning library."

Kaolin, the PyTorch library presented by Jatavallabhula and his colleagues, contains a variety of tools for constructing deep learning architectures that can analyze 3-D data, which are both efficient and easy to use. It also allows researchers to load, preprocess, and manipulate 3-D data before it is used to train deep learning algorithms.  .... "