Figure 1. Our deep generative network DSM-Net encodes 3D shapes with complex structure and fine geometry in a representation that leverages the synergy between geometry and structure, while disentangling these two aspects as much as possible. This enables novel modes of controllable generation for high-quality shapes. Left: results of disentangled interpolation. Here, the top left and bottom right chairs (highlighted with red rectangles) are the input shapes. The remaining chairs are generated automatically with our DSM-Net, where in each row, the structure of the shapes is interpolated while keeping the geometry unchanged, whereas in each column, the geometry is interpolated while retaining the structure. Right: shape generation results with complex structure and fine geometry details by our DSM-Net. We show close-up views in dashed yellow rectangles to highlight local details.
We introduce DSM-Net, a deep neural network that learns a disentangled structured mesh representation for 3D shapes, where two key aspects of shapes, geometry and structure, are encoded in a synergistic manner to ensure plausibility of the generated shapes, while also being disentangled as much as possible. This supports a range of novel shape generation applications with intuitive control, such as interpolation of structure (geometry) while keeping geometry (structure) unchanged.
Our team: Jie Yang*, Kaichun Mo*, Yu-Kun Lai, Leonidas J. Guibas and Lin Gao from Institute of Computing Technology, CAS and University of Chinese Academy of Sciences, Stanford University, Cardiff University.
* equal contribution.
Provisional Accept with Major Revisions, ACM Transactions on Graphics 2021
Arxiv Version: https://arxiv.org/abs/2008.05440
Project Page: http://geometrylearning.com/dsg-net/
This repository provides data and code as follows.
data/ # contains data, models, results, logs
code/ # contains code and scripts
# please follow `code/README.md` to run the code
stats/ # contains helper statistics
- The whole dataset is uploaded, you can find it from here.
Please post issues for questions and more helps on this Github repo page. We encourage using Github issues instead of sending us emails since your questions may benefit others.
MIT Licence