
videogigagan-pytorch
Implementation of VideoGigaGAN, SOTA video upsampling out of Adobe AI labs, in Pytorch
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Video GigaGAN - Pytorch is an implementation of Video GigaGAN, a state-of-the-art video upsampling technique developed by Adobe AI labs. The project aims to provide a Pytorch implementation for researchers and developers interested in video super-resolution. The codebase allows users to replicate the results of the original research paper and experiment with video upscaling techniques. The repository includes the necessary code and resources to train and test the GigaGAN model on video datasets. Researchers can leverage this implementation to enhance the visual quality of low-resolution videos and explore advancements in video super-resolution technology.
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Implementation of Video GigaGAN, SOTA video upsampling out of Adobe AI labs, in Pytorch
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@article{xu2024videogigagan,
title = {VideoGigaGAN: Towards Detail-rich Video Super-Resolution},
author = {Yiran Xu and Taesung Park and Richard Zhang and Yang Zhou and Eli Shechtman and Feng Liu and Jia-Bin Huang and Difan Liu},
year = {2024},
eprint = {2404.12388},
archivePrefix = {arXiv},
primaryClass = {cs.CV}
}
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