Trainner
traiNNer: Deep learning framework for image and video super-resolution, restoration and image-to-image translation, for training and testing.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Anime4k | 17,264 | 4 months ago | 97 | mit | Jupyter Notebook | |||||
| A High-Quality Real Time Upscaler for Anime Video | ||||||||||
| Image Super Resolution | 4,392 | 4 months ago | 106 | apache-2.0 | Python | |||||
| 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks. | ||||||||||
| Srgan | 3,197 | 2 months ago | 137 | Python | ||||||
| Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | ||||||||||
| Srgan Tensorflow | 694 | 4 years ago | 43 | mit | Python | |||||
| Tensorflow implementation of the SRGAN algorithm for single image super-resolution | ||||||||||
| Fast Srgan | 559 | a year ago | 3 | mit | Python | |||||
| A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps | ||||||||||
| Srcnn Tensorflow | 435 | 4 years ago | 28 | mit | Python | |||||
| Image Super-Resolution Using Deep Convolutional Networks in Tensorflow https://arxiv.org/abs/1501.00092v3 | ||||||||||
| Pytorch Srgan | 348 | 6 years ago | 7 | gpl-3.0 | Python | |||||
| A modern PyTorch implementation of SRGAN | ||||||||||
| Srmd | 345 | 3 years ago | 18 | MATLAB | ||||||
| Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018) (Matlab) | ||||||||||
| Espcn | 260 | 4 years ago | Python | |||||||
| A PyTorch implementation of ESPCN based on CVPR 2016 paper "Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network" | ||||||||||
| Iseebetter | 223 | 3 years ago | 10 | mit | C++ | |||||
| iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press | ||||||||||
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