Deep-Exemplar-based-Video-Colorization
OASIS
| Deep-Exemplar-based-Video-Colorization | OASIS | |
|---|---|---|
| 4 | 1 | |
| 346 | 322 | |
| 0.0% | - | |
| 0.0 | 10.0 | |
| over 2 years ago | over 2 years ago | |
| Python | Python | |
| MIT License | GNU Affero General Public License v3.0 |
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Deep-Exemplar-based-Video-Colorization
- [Machine Learning] [R] colorisation vidéo basée sur un exemple
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Show HN: I made a new AI colorizer
Thanks! yeah, a few people have used the tool to colorize videos, frame by frame. For example Lord of the flies (1963): https://www.dailymotion.com/video/x8eiho4
Although, I'd recommend colorizing a few key frames and then use https://github.com/zhangmozhe/Deep-Exemplar-based-Video-Colo...
Cool, yeah, my next model will be better for comic books. You can also use the 'Surprise Me' button in the editor and you'll get some decent results.
- 1929 video from Shanghai, upscaled to 4K color using AI
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[P] Colorizing the legacy videos with attention mechanism
We recently released the code for our paper "Deep Exemplar-based Video Colorization". The code along with the Colab demo is available at: https://github.com/zhangmozhe/Deep-Exemplar-based-Video-Colorization. Welcome to have a try.
OASIS
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StyleGAN-NADA: Blind Training and Other Wonders
Conclusion So this is how StyleGAN-NADA, a CLIP-guided zero-shot method for Non-Adversarial Domain Adaptation of image generators, works. Although the StyleGAN-NADA is focused on StyleGAN, it can be applied to other generative architectures such as OASIS and many others.
What are some alternatives?
mmagic - OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.
VLDet - [ICLR 2023] PyTorch implementation of VLDet （https://arxiv.org/abs/2211.14843）
CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Keras-GAN - Keras implementations of Generative Adversarial Networks.
ArtGAN - ArtGAN + WikiArt: This work presents a series of new approaches to improve GAN for conditional image synthesis and we name the proposed model as “ArtGAN”.
AdamP - AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)