TextureGeneration: GitHub File Free Download

Re-ID Supervised Texture Generation

This is the code repo for the paper Re-Identification Supervised Texture Generation (CVPR2019) [PDF].


  • Python 3.6
  • Pytorch 0.4.1

Install other python packages via:

pip install -r requirements.txt


  • Download the pretrained weight

  • Set the “model_path” in demo.sh to the path of pretrained weight

  • Put some pedestrian images to example_results/input

  • Run demo.sh

bash demo.sh
  • Get the resulting textures from example_results/texture

  • Render the 3D human model with texture using:


  1. Download datasets:

    • market-1501
    • CUHK-SYSU (for background)
    • PRW (for background)
  2. Generate the rendering tensors with RenderingTensorGenerator.

  3. Get the pretrained re-id network.

  4. Set all paths and parameters in config.py

  5. start train

bash train.sh
  1. you will get the trained models in model_log_path


If you use this code for your research, please cite our paper.

  title={Re-Identification Supervised Texture Generation},
  author={Jian, Wang and Yunshan, Zhong and Yachun, Li and Chi, Zhang and Yichen, Wei},
  journal={IEEE Conference on Computer Vision and Pattern Recognition},

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