Manypriors
Reference PyTorch implementation of "End-to-end optimized image compression with competition of prior distributions"
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Srec | 918 | 2 years ago | 8 | mit | Python | |||||
| PyTorch Implementation of "Lossless Image Compression through Super-Resolution" | ||||||||||
| Waifu2x Extension | 135 | 4 years ago | 2 | other | Python | |||||
| Image, GIF and Video enlarger/upscaler achieved with waifu2x and Anime4K. [NO LONGER UPDATED] | ||||||||||
| Cool Chic | 47 | 4 months ago | bsd-3-clause | Python | ||||||
| Cool-chic is a low-complexity neural image codec based on overfitting, competitive with VVC. | ||||||||||
| Image Compression Benchmarking | 36 | 8 years ago | 1 | wtfpl | Python | |||||
| Image compression codecs benchmark inspired by Google's "Full Resolution Image Compression with Recurrent Neural Networks" | ||||||||||
| Nn 2003 | 14 | 8 years ago | C | |||||||
| 2003 Neural Networks experiments -- when it was not mainstream ;-) | ||||||||||
| Neural Networks For Image Compression | 9 | 7 years ago | Jupyter Notebook | |||||||
| Image compression using neural networks | ||||||||||
| Context_adaptive_neural_network_based_prediction | 8 | 4 years ago | 1 | C++ | ||||||
| Context-adaptive neural network based prediction for image compression https://arxiv.org/abs/1807.06244 | ||||||||||
| Machine Learning Project For Image Compression | 7 | 3 years ago | Jupyter Notebook | |||||||
| Implementation & Learning of Compression of Image through use of K-means Clustering Algorithm | ||||||||||
| Annimagecompression | 6 | 7 years ago | C++ | |||||||
| Artificial Neural Networks (ANN) Image Compression | ||||||||||
| Manypriors | 6 | 10 months ago | gpl-3.0 | Python | ||||||
| Reference PyTorch implementation of "End-to-end optimized image compression with competition of prior distributions" | ||||||||||
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