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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Bringing Old Photo Back to Life (CVPR 2020 oral)
| Date | Stars |
|---|---|
| 2026-07-24 | 15700 |
| 2026-07-25 | 15700 |
| 2026-07-28 | 15700 |
| 2026-07-30 | 15700 |
| 2026-08-06 | 15700 |
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# Old Photo Restoration (Official PyTorch Implementation) <img src='imgs/0001.jpg'/> ### [Project Page](http://raywzy.com/Old_Photo/) | [Paper (CVPR version)](https://arxiv.org/abs/2004.09484) | [Paper (Journal version)](https://arxiv.org/pdf/2009.07047v1.pdf) | [Pretrained Model](https://hkustconnect-my.sharepoint.com/:f:/g/personal/bzhangai_connect_ust_hk/Em0KnYOeSSxFtp4g_dhWdf0BdeT3tY12jIYJ6qvSf300cA?e=nXkJH2) | [Colab Demo](https://colab.research.google.com/drive/1NEm6AsybIiC5TwTU_4DqDkQO0nFRB-uA?usp=sharing) | [Replicate Demo & Docker Image](https://replicate.ai/zhangmozhe/bringing-old-photos-back-to-life) :fire: **Bringing Old Photos Back to Life, CVPR2020 (Oral)** **Old Photo Restoration via Deep Latent Space Translation, TPAMI 2022** [Ziyu Wan](http://raywzy.com/)<sup>1</sup>, [Bo Zhang](https://www.microsoft.com/en-us/research/people/zhanbo/)<sup>2</sup>, [Dongdong Chen](http://www.dongdongchen.bid/)<sup>3</sup>, [Pan Zhang](https://panzhang0212.github.io/)<sup>4</sup>, [Dong Chen](https://www.microsoft.com/en-us/research/people/doch/)<sup>2</sup>, [Jing Liao](https://liaojing.github.io/html/)<sup>1</sup>, [Fang Wen](https://www.microsoft.com/en-us/research/people/fangwen/)<sup>2</sup> <br> <sup>1</sup>City University of Hong Kong, <sup>2</sup>Microsoft Research Asia, <sup>3</sup>Microsoft Cloud AI, <sup>4</sup>USTC <!-- ## Notes of this project The code originates from our research project and the aim is to demonstrate the research idea, so we have not optimized it from a product perspective. And we will spend time to address some common issues, such as out of memory issue, limited resolution, but will not involve too much in engineering problems, such as speedup of the inference, fastapi deployment and so on. **We welcome volunteers to contribute to this project to make it more usable for practical application.** --> ## :sparkles: News **2022.3.31**: Our new work regarding old film restoration will be published in CVPR 2022. For more details, please refer to the [project website](http://raywzy.com/Old_Film/) and [github repo](https://github.com/raywzy/Bringing-Old-Films-Back-to-Life). The framework now supports the restoration of high-resolution input. <img src='imgs/HR_result.png'> Training code is available and welcome to have a try and learn the training details. You can now play with our [Colab](https://colab.research.google.com/drive/1NEm6AsybIiC5TwTU_4DqDkQO0nFRB-uA?usp=sharing) and try it on your photos. ## Requirement The code is tested on Ubuntu with Nvidia GPUs and CUDA installed. Python>=3.6 is required to run the code. ## Installation Clone the Synchronized-BatchNorm-PyTorch repository for ``` cd Face_Enhancement/models/networks/ git clone https://github.com/vacancy/Synchronized-BatchNorm-PyTorch cp -rf Synchronized-BatchNorm-PyTorch/sync_batchnorm . cd ../../../ ``` ``` cd Global/detection_models git clone https://github.com/vacancy/Synchronized-BatchNorm-PyTorch cp -rf Synchronized-BatchNorm-PyTorch/sync_batchnorm . cd ../../ ``` Download the landmark detection pretrained model ``` cd Face_Detection/ wget http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2 bzip2 -d shape_predictor_68_face_landmarks.dat.bz2 cd ../ ``` Download the pretrained model, put the file `Face_Enhancement/checkpoints.zip` under `./Face_Enhancement`, and put the file `Global/checkpoints.zip` under `./Global`. Then unzip them respectively. ``` cd Face_Enhancement/ wget https://github.com/microsoft/Bringing-Old-Photos-Back-to-Life/releases/download/v1.0/face_checkpoints.zip unzip face_checkpoints.zip cd ../ cd Global/ wget https://github.com/microsoft/Bringing-Old-Photos-Back-to-Life/releases/download/v1.0/global_checkpoints.zip unzip global_checkpoints.zip cd ../ ``` Install dependencies: ```bash pip install -r requirements.txt ``` ## :rocket: How to use? **Note**: GPU can be set 0 or 0,1,2 or 0,2; use -1 for CPU ### 1) Full Pipeline You could easily restore the old photos with one simple co
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6ad18e01c1f94d80, topic:pytorch