{"id":13906020,"url":"https://github.com/Ha0Tang/SelectionGAN","last_synced_at":"2025-07-18T03:32:58.743Z","repository":{"id":73825380,"uuid":"181239377","full_name":"Ha0Tang/SelectionGAN","owner":"Ha0Tang","description":"[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image 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\n[![License CC BY-NC-SA 4.0](https://img.shields.io/badge/license-CC4.0-blue.svg)](https://github.com/Ha0Tang/SelectionGAN/blob/master/LICENSE.md)\n![Python 3.6](https://img.shields.io/badge/python-3.6-green.svg)\n![Packagist](https://img.shields.io/badge/Pytorch-0.4.1-red.svg)\n![Last Commit](https://img.shields.io/github/last-commit/Ha0Tang/SelectionGAN)\n[![Maintenance](https://img.shields.io/badge/Maintained%3F-yes-blue.svg)](https://github.com/Ha0Tang/SelectionGAN/graphs/commit-activity)\n![Contributing](https://img.shields.io/badge/contributions-welcome-red.svg?style=flat)\n![Ask Me Anything !](https://img.shields.io/badge/Ask%20me-anything-1abc9c.svg)\n\n# SelectionGAN for Guided Image-to-Image Translation\n### [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)\n\n![SelectionGAN Results](./imgs/motivation.jpg)\n\n## Citation\nIf you use this code for your research, please cite our papers.\n```\n@article{tang2022multi,\n  title={Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation},\n  author={Tang, Hao and Torr, Philip HS and Sebe, Nicu},\n  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},\n  year={2022}\n}\n\n@inproceedings{tang2019multi,\n  title={Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation},\n  author={Tang, Hao and Xu, Dan and Sebe, Nicu and Wang, Yanzhi and Corso, Jason J. and Yan, Yan},\n  booktitle={CVPR},\n  year={2019}\n}\n\n@article{tang2023edge,\n  title={Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis},\n  author={Tang, Hao and Qi, Xiaojuan and Sun, Guolei, and Xu, Dan and and Sebe, Nicu and Timofte, Radu and Van Gool, Luc},\n  journal={ICLR},\n  year={2023}\n}\n\n@article{tang2022local,\n  title={Local and Global GANs with Semantic-Aware Upsampling for Image Generation},\n  author={Tang, Hao and Shao, Ling and Torr, Philip HS and Sebe, Nicu},\n  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},\n  year={2022}\n}\n\n@inproceedings{tang2020local,\n  title={Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation},\n  author={Tang, Hao and Xu, Dan and Yan, Yan and Torr, Philip HS and Sebe, Nicu},\n  booktitle={CVPR},\n  year={2020}\n}\n\n@article{wu2022cross,\n  title={Cross-view panorama image synthesis with progressive attention GANs},\n  author={Wu, Songsong and Tang, Hao and Jing, Xiao-Yuan and Qian, Jianjun and Sebe, Nicu and Yan, Yan and Zhang, Qinghua},\n  journal={Elsevier Pattern Recognition (PR)},\n  year={2022}\n}\n\n@article{wu2022cross,\n  title={Cross-View Panorama Image Synthesis},\n  author={Wu, Songsong and Tang, Hao and Jing, Xiao-Yuan and Zhao, Haifeng and Qian, Jianjun and Sebe, Nicu and Yan, Yan},\n  journal={IEEE Transactions on Multimedia (TMM)},\n  year={2022}\n}\n\n@inproceedings{ren2021cascaded,\n  title={Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation},\n  author={Ren, Bin and Tang, Hao and Sebe, Nicu},\n  booktitle={BMVC},\n  year={2021}\n}\n```\n\nIn the meantime, check out our related papers:\n- cross-view image translation: \n  - [Cross-View Panorama Image Synthesis (TMM 2022)](https://github.com/sswuai/PanoGAN)\n  - [Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation (BMVC 2021 Oral)](https://github.com/Amazingren/CrossMLP)\n- person image generation: \n  - [XingGAN for Person Image Generation (ECCV 2020)](https://github.com/Ha0Tang/XingGAN)\n  - [Bipartite Graph Reasoning GANs for Person Image Generation (BMVC 2020 Oral)](https://github.com/Ha0Tang/BiGraphGAN)\n- semantic image synthesis: \n  - [Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis (ICLR 2023)](https://github.com/Ha0Tang/ECGAN)\n  - [Dual Attention GANs for Semantic Image Synthesis (ACM MM 2020)](https://github.com/Ha0Tang/DAGAN)\n  - [Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation (CVPR 2020)](https://github.com/Ha0Tang/LGGAN)\n\nMore related guided image-to-image translation papers can be found in [this page](https://github.com/Ha0Tang/Guided-I2I-Translation-Papers).\n\n## To Do List\n- [x] SelectionGAN: CVPR version\n- [x] SelectionGAN++: TPAMI version\n- [x] Pix2pix++: Takes RGB image and target semantic map as inputs: [code](./cross_view_v2)\n- [x] X-ForK++: Takes RGB image and target semantic map as inputs: [code](./cross_view_v2)\n- [x] X-Seq++: Takes RGB image and target semantic map as inputs: [code](./cross_view_v2)\n\n## Others\n- [How to write a great science paper](https://www.nature.com/articles/d41586-019-02918-5)\n\n## Acknowledgments\nThis source code is inspired by [Pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix).\n\n## Contributions\nIf 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)).\n\n## Collaborations\nI'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).\n___\n*In life, patience is the key. It's much better to be going somewhere slowly than nowhere fast.*\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FHa0Tang%2FSelectionGAN","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FHa0Tang%2FSelectionGAN","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FHa0Tang%2FSelectionGAN/lists"}