This repository is by Yanwu Xu and contains the PyTorch source code to reproduce the experiments in our CVPR2022 paper Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation by Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong* and Kayhan Batmanghelich* (* Equal Contribution)
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Face Pose Transfer data can be downloaded here
To run the code on the face pose transfer data. 1. download the data from above link 2. unzip the data to the ./data folder 3. sh run_gcpert.sh
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@InProceedings{Xu_2022_CVPR,
author = {Xu, Yanwu and Xie, Shaoan and Wu, Wenhao and Zhang, Kun and Gong, Mingming and Batmanghelich, Kayhan},
title = {Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2022},
pages = {18311-18320}
}
This work was partially supported by NIH Award Number 1R01HL141813-01, NSF 1839332 Tripod+X, SAP SE, and Pennsylvania Department of Health. We are grateful for the computational resources provided by Pittsburgh SuperComputing grant number TG-ASC170024. MG is supported by Australian Research Council Project DE210101624. KZ would like to acknowledge the support by the National Institutes of Health (NIH) under Contract R01HL159805, by the NSF-Convergence Accelerator Track-D award #2134901, and by the United States Air Force under Contract No. C7715.