Skip to content


Folders and files

Last commit message
Last commit date

Latest commit



19 Commits

Repository files navigation


Adversarial Texture Optimization from RGB-D Scans (CVPR 2020).

AdversarialTexture Teaser

Scanning Data Download

Please refer to data directory for details.

Before run following scripts, please modify the data_path in src/ as the absolute path of the data folder (e.g. Adversarial/data) where you download all data.

Prepare for Training (Optimization)

Please refer to src/preprocessing directory for details.

Run Training (Optimization)

Consider execute in parallel.

cd src/textureoptim

Result Visualization

The result will be stored in data/result/chairID/chairID.png. You can use them to replace the corresponding default texture in data/shape, and use meshlab to open obj files to see the results.

Alternatively, we provide a simple script to render results. You will be able to see the rendering comparison in data/visual.

cd src


© Jingwei Huang, Stanford University

IMPORTANT: If you use this code please cite the following in any resulting publication:

  title={Adversarial Texture Optimization from RGB-D Scans},
  author={Huang, Jingwei and Thies, Justus and Dai, Angela and Kundu, Abhijit and Jiang, Chiyu and Guibas, Leonidas J and Niessner, Matthias and Funkhouser, Thomas},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},

The rendering process is a modification of pyRender.