Deep-Exemplar-based-Video-Colorization
OASIS
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| Deep-Exemplar-based-Video-Colorization | OASIS | |
|---|---|---|
| 4 | 1 | |
| 330 | 309 | |
| - | 0.0% | |
| 0.0 | 10.0 | |
| over 1 year ago | over 1 year 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?
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.
Few-Shot-Patch-Based-Training - The official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
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.
AdamP - AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)
TraVeLGAN_with_perceptual_loss - The implementation code of Thesis project which entitled "Photo-to-Emoji Transformation with TraVeLGAN and Perceptual Loss" as a final project in my master study.
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
HyperGAN - Composable GAN framework with api and user interface
clean-fid - PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]
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”.
anycost-gan - [CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing