Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency

Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency

Code for the paper Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency (NeurIPS 2020).

Requirements

• Python 3.6
• Pytorch 1.4

To install Neural Mesh Renderer and Perceptual loss:

cd external
sh install_external.sh

Demo

• Download the trained model.
• Extract and put the model in cachedir/snapshots
• Run the demo:

sh ./HPBTT/run_demo_market.sh <model_name> <epoch_num> <input_image_name>

Training

To train the model:

python -m HPBTT.experiments.train_market --name <model_name>

Evaluation

To evaluate the model:

sh ./HPBTT/run_eval_market.sh <model_name> <epoch_num> <output_image_path>

Acknowledgement

Our code is based on cmr.

Citation

If you use this code for your research, please consider citing:

@inproceedings{zhao2020human,
  title={Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency},
  author={Zhao, Fang and Liao, Shengcai and Zhang, Kaihao and Shao, Ling},
  booktitle={Advances in Neural Information Processing Systems},
  year={2020}
}