Pose-Guided Person Image Synthesis in the Non-iconic Views

This is the code for TIP paper 'Pose-Guided Person Image Synthesis in the Non-iconic Views'. To run this code, you need to do as follows,

Prepare the environment

This code needs pytorch 1.4.0.

We provide the processed frames, poses and segmentations for Penn Action and BBC-Pose. Market-1501 is the same as the one used in PATN.

python pose_to_image.py -n debug -R -nl -dp -d {Penn_Action/bbcpose/market1501} -dr {your_data_root}

python inference.py --dr {your_data_root} -n {name of model} -dp -nl

Then you will have the generated images in ./result_images/{dataset}/{name of model}.

We provide several metrics in ./metrics including Inception Score, FID, SSIM and M-SSIM.

You need to modify the variable dataset and root to your own setting, and run

python inception_score.py
python compute_ssim.py
python fid_score.py -c {gpu}

The scripts will evaluate the generated images from all models in the chosen dataset.