O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis

Understand

We present O-CNN, an Octree-based Convolutional Neural Network (CNN) for 3D shape analysis.

• Built upon the octree representation of 3D shapes, our method takes the average normal vectors of a 3D model sampled in the finest leaf octants as input and performs 3D CNN operations on the octants occupied by the 3D shape surface.
• We design a novel octree data structure to efficiently store the octant information and CNN features into the graphics memory and execute the entire O-CNN training and evaluation on the GPU.
• O-CNN supports various CNN structures and works for 3D shapes in different representations.