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Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis, including
human motion imitation, appearance transfer, and novel view synthesis. Currently the paper is under review of
IEEE TPAMI. It is an extension of our previous ICCV project impersonator,
and it has a more powerful ability in generalization and produces higher-resolution results (512 x 512, 1024 x 1024) than the previous ICCV version.
See more details, including system dependencies, python requirements and setups in install.md.
Please follows the instructions in install.md to install this firstly.
Notice that imags_size=512 need at least 9.8GB GPU memory. if you are using a middle-level GPU(e.g. RTX 2060), you should change the image_size to 384 or 256. The following table can be used as a reference:
@article{liu2021liquid,
title={Liquid warping GAN with attention: A unified framework for human image synthesis},
author={Liu, Wen and Piao, Zhixin and Tu, Zhi and Luo, Wenhan and Ma, Lin and Gao, Shenghua},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
year={2021},
publisher={IEEE}
}
@InProceedings{lwb2019,
title={Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis},
author={Wen Liu and Zhixin Piao, Min Jie, Wenhan Luo, Lin Ma and Shenghua Gao},
booktitle={The IEEE International Conference on Computer Vision (ICCV)},
year={2019}
}
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Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis