/PCDMs

Implementation code:Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

Primary LanguagePythonMIT LicenseMIT

PCDMs

Implementation code:Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

Generated Results

PCDMs Motivation

You can directly download our test results from Google Drive: (1) PCDMs vs SOTA (2) PCDMs Results.

The PCDMs vs SOTA compares our method with several state-of-the-art methods e.g. ADGAN, PISE, GFLA, DPTN, CASD, NTED, PIDM. Each row contains target_pose, source_image, ground_truth, ADGAN, PISE, GFLA, DPTN, CASD, NTED, PIDM, and PCDMs (ours) respectively.

Methods

PCDMs Motivation

PCDMs Framework

Dataset

Processed Data

This link contains processed and prepared data that is ready for use. The data has been processed in the following ways:

• Rename image

• Split the train/test set

• keypoints extracted with Openpose

The folder structure of dataset should be as follows:

Deepfashion/
├── all_data_png                        # including train and test images
│   ├── img1.png          
│   ├── ...
│   ├── img52712.png         
├── train_lst_256_png                   # including train images of 256 size
│   ├── img1.png
│   ├── ...
│   ├── img48674.png
├── train_lst_512_png                   # including train images of 512 size
│   ├── img1.png
│   ├── ...
│   ├── img48674.png
├── test_lst_256_png                    # including test images of 256 size
│   ├── img1.png
│   ├── ...
│   ├── img4038.png
├── test_lst_512_png                    # including test images of 512 size
│   ├── img1.png
│   ├── ...
│   ├── img4038.png
├── normalized_pose_txt.zip             # including pose coordinate of train and test set
│   ├── pose_coordinate1.txt
│   ├── ...
│   ├── pose_coordinate40160.txt
├── train_data.json                     
├── test_data.json

Original Data

Download img_highres.zip of the DeepFashion Dataset from In-shop Clothes Retrieval Benchmark.

Unzip img_highres.zip. You will need to ask for password from the dataset maintainers.

Checkpoints Links

We provide 3 stage checkpoints available here.

TO DO

Released the train and test code at this.

Citation

If this work is useful to you, please consider citing our paper:

@article{shen2023advancing,
  title={Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models},
  author={Shen, Fei and Ye, Hu and Zhang, Jun and Wang, Cong and Han, Xiao and Yang, Wei},
  journal={arXiv preprint arXiv:2310.06313},
  year={2023}
}