May 5, 2022 · We present an adaptive deep representation of volumetric fields of 3D shapes and an efficient approach to learn this deep representation for high-quality 3D ...
This repository contains the implementation of our papers Dual Octree Graph Networks. The experiments are conducted on Ubuntu 18.04 with 4 V400 GPUs (32GB ...
Jul 22, 2022 · An encoder-decoder network is designed to learn the adaptive feature volume based on the graph convolutions over the dual graph of octree nodes.
Dual Octree Graph Networks for Learning. Adaptive Volumetric Shape Representations. Peng-Shuai Wang. Yang Liu. Xin Tong. Microsoft Research Asia. ACM ...
May 5, 2022 · We present an adaptive deep representation of volumetric fields of 3D shapes and an efficient approach to learn this deep representation for ...
Oct 22, 2024 · We present an adaptive deep representation of volumetric fields of 3D shapes and an efficient approach to learn this deep representation for ...
Our method effectively encodes shape details, enables fast 3D shape reconstruction, and exhibits good generality for modeling 3D shapes out of training ...
May 6, 2022 · Dual Octree Graph Networks for Learning Adaptive Volumetric Shape Representations abs: https://arxiv.org/abs/2205.02825.
Dual Octree Graph Networks for Learning Adaptive Volumetric Shape Representations. octree-nn/DualOctreeGNN's past year of commit activity. Python 0 MIT 16 0 0 ...
Our method encodes the volumetric field of a 3D shape with an adaptive feature volume organized by an octree and applies a compact multilayer perceptron network ...