Meta AI has released Implicitron, a modular framework for neural implicit representations in the PyTorch3D library.
The Meta AI team announced the release of Implicitron, a new modular framework for implicit neural representation in the team's open-source PyTorch3D library. Being created and released to advance research on the topic, Implicitron provides abstractions and implementations of popular implicit representations and rendering components to allow for easy experimentation.
According to the team, the new framework simplifies the process of evaluating variations, combinations, and modifications of various NeRF-based methods with a common codebase that doesn’t require expertise in 3D or graphics. Thanks to its modular architecture, Implicitron allows people to easily combine the contributions of different papers and replace specific components to test new ideas.
"It is crucial to have better tools that can take image data and create accurate 3D reconstructions in order to accelerate research in AR/VR. This allows for useful real-world applications, like enabling people to try clothing on virtually when shopping in AR and VR or to relive memorable moments from different perspectives," commented the team. "By integrating this framework within the popular PyTorch3D library for 3D deep learning, already widely used by researchers in the field, Meta aims to give people using the framework a way to easily install and import components from Implicitron into their projects without needing to reimplement or copy the code."