huage001 / adaattn

Arbitrary Neural Style Transfer

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Run time and cost

This model costs approximately $0.00026 to run on Replicate, or 3846 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 2 seconds. The predict time for this model varies significantly based on the inputs.

Readme

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

Overview

This repository contains the officially unofficial PyTorch re-implementation of paper:

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer,

Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Meiling Wang, Xin Li, Zhengxing Sun, Qian Li, Errui Ding

ICCV 2021

Citation

If you find ideas or codes useful for your research, please cite:

```
@inproceedings{liu2021adaattn,
  title={AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer},
  author={Liu, Songhua and Lin, Tianwei and He, Dongliang and Li, Fu and Wang, Meiling and Li, Xin and Sun, Zhengxing and Li, Qian and Ding, Errui},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  year={2021}
}
```

Acknowledgments

This implementation is developed based on the code framework of pytorch-CycleGAN-and-pix2pix by Junyan Zhu et al.