PCDMs

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

Generated Results

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

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}
}

muzishen/PCDMs