Facebook launches 3D deep learning library for PyTorch
Facebook disclosed PyTorch, is also open-sourcing Mesh R-CNN model introduced last year capable of rendering 3D objects from 2D shapes in images of interior spaces.
PyTorch is enables researchers and developers to combine deep learning and 3D objects. It was inspired by Mesh R-CNN and recent 3D work by Facebook AI Research, FAIR engineer Nikhila Ravi said.
FAIR (Facebook AI Research) used to tackle AI challenges like robotic grasping or helping autonomous vehicles understand the position of nearby objects, PyTorch usually comes with frequently used 3D operators and a differentiable mesh renderer for creating 3D objects and loss functions for 3D data, it greatly reduces on the time to work on 3D planning research.
Ravi told, PyTorch3D also has a differentiable rendering API, some CUDA support, and heterogeneous batching capabilities unavailable in any existing 3D library.
It also used a patch tensor to collapse all vertices for meshes in a batch into a single tensor involved with batching, a common process for deep learning research and in the last year the launch of the PyRobot robotics framework follows, and FAIR 3D research that extracts characters from real-world videos.
