SelectionGAN

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[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation

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# SelectionGAN for Guided Image-to-Image Translation
### [CVPR Paper](https://arxiv.org/abs/1904.06807) | [TPAMI Paper](https://arxiv.org/abs/2002.01048) | [Guided-I2I-Translation-Papers](https://github.com/Ha0Tang/Guided-I2I-Translation-Papers)

![SelectionGAN Results](https://raw.githubusercontent.com/Ha0Tang/SelectionGAN/master/imgs/motivation.jpg)

## Citation
If you use this code for your research, please cite our papers.
```
@article{tang2022multi,
  title={Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation},
  author={Tang, Hao and Torr, Philip HS and Sebe, Nicu},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year={2022}
}

@inproceedings{tang2019multi,
  title={Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation},
  author={Tang, Hao and Xu, Dan and Sebe, Nicu and Wang, Yanzhi and Corso, Jason J. and Yan, Yan},
  booktitle={CVPR},
  year={2019}
}

@article{tang2023edge,
  title={Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis},
  author={Tang, Hao and Qi, Xiaojuan and Sun, Guolei, and Xu, Dan and and Sebe, Nicu and Timofte, Radu and Van Gool, Luc},
  journal={ICLR},
  year={2023}
}

@article{tang2022local,
  title={Local and Global GANs with Semantic-Aware Upsampling for Image Generation},
  author={Tang, Hao and Shao, Ling and Torr, Philip HS and Sebe, Nicu},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year={2022}
}

@inproceedings{tang2020local,
  title={Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation},
  author={Tang, Hao and Xu, Dan and Yan, Yan and Torr, Philip HS and Sebe, Nicu},
  booktitle={CVPR},
  year={2020}
}

@article{wu2022cross,
  title={Cross-view panorama image synthesis with progressive attention GANs},
  author={Wu, Songsong and Tang, Hao and Jing, Xiao-Yuan and Qian, Jianjun and Sebe, Nicu and Yan, Yan and Zhang, Qinghua},
  journal={Elsevier Pattern Recognition (PR)},
  year={2022}
}

@article{wu2022cross,
  title={Cross-View Panorama Image Synthesis},
  author={Wu, Songsong and Tang, Hao and Jing, Xiao-Yuan and Zhao, Haifeng and Qian, Jianjun and Sebe, Nicu and Yan, Yan},
  journal={IEEE Transactions on Multimedia (TMM)},
  year={2022}
}

@inproceedings{ren2021cascaded,
  title={Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation},
  author={Ren, Bin and Tang, Hao and Sebe, Nicu},
  booktitle={BMVC},
  year={2021}
}
```

In the meantime, check out our related papers:
- cross-view image translation: 
  - [Cross-View Panorama Image Synthesis (TMM 2022)](https://github.com/sswuai/PanoGAN)
  - [Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation (BMVC 2021 Oral)](https://github.com/Amazingren/CrossMLP)
- person image generation: 
  - [XingGAN for Person Image Generation (ECCV 2020)](https://github.com/Ha0Tang/XingGAN)
  - [Bipartite Graph Reasoning GANs for Person Image Generation (BMVC 2020 Oral)](https://github.com/Ha0Tang/BiGraphGAN)
- semantic image synthesis: 
  - [Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis (ICLR 2023)](https://github.com/Ha0Tang/ECGAN)
  - [Dual Attention GANs for Semantic Image Synthesis (ACM MM 2020)](https://github.com/Ha0Tang/DAGAN)
  - [Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation (CVPR 2020)](https://github.com/Ha0Tang/LGGAN)

More related guided image-to-image translation papers can be found in [this page](https://github.com/Ha0Tang/Guided-I2I-Translation-Papers).

## To Do List
- [x] SelectionGAN: CVPR version
- [x] SelectionGAN++: TPAMI version
- [x] Pix2pix++: Takes RGB image and target semantic map as inputs: [code](./cross_view_v2)
- [x] X-ForK++: Takes RGB image and target semantic map as inputs: [code](./cross_view_v2)
- [x] X-Seq++: Takes RGB image and target semantic map as inputs: [code](./cross_view_v2)

## Others
- [How to write a great science paper](https://www.nature.com/articles/d41586-019-02918-5)

## Acknowledgments
This source code is inspired by [Pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix).

## Contributions
If you have any questions/comments/bug reports, feel free to open a github issue or pull a request or e-mail to the author Hao Tang ([bjdxtanghao@gmail.com](bjdxtanghao@gmail.com)).

## Collaborations
I'm always interested in meeting new people and hearing about potential collaborations. If you'd like to work together or get in contact with me, please email bjdxtanghao@gmail.com. Some of our projects are listed [here](https://github.com/Ha0Tang).
___
*In life, patience is the key. It's much better to be going somewhere slowly than nowhere fast.*

SelectionGAN

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