Dec 5, 2017 · We present O-CNN, an Octree-based Convolutional Neural Network (CNN) for 3D shape analysis. Built upon the octree representation of 3D shapes.
We present O-CNN, an Octree-based Convolutional Neural Network (CNN) for 3D shape analysis. Built upon the octree representation of 3D shapes.
microsoft/O-CNN: O-CNN: Octree-based Convolutional Neural ... - GitHub
github.com › microsoft › O-CNN
This repository contains the implementation of our papers related with O-CNN. The code is released under the MIT license.
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 ...
O-CNN is an octree-based 3D convolutional neural network framework for 3D data. O-CNN constrains the CNN storage and computation into non-empty sparse voxels ...
4 days ago · We compare the performance of the O-CNN with other existing 3D CNN solutions and demonstrate the efficiency and efficacy of O-CNN in three shape ...
We present an Adaptive Octree-based Convolutional Neural Network (Adaptive O-CNN) for efficient 3D shape encoding and decoding.
People also ask
What is the difference between CNN and 3D CNN?
What is a 3D convolutional neural network?
What is convolutional neural networks CNN for image analysis?
How to train 3D CNN?
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 ...
We present an Adaptive Octree-based Convolutional Neural Network (Adaptive O-CNN) for efficient 3D shape encoding and decoding.
We show that with these simple adaptions — output-guided skip-connection and deeper O-CNN (up to 70 layers), our network achieves state-of-the-art results in 3D.