TraVeLGAN_with_perceptual_loss
Deep-Exemplar-based-Video-Colorization
| TraVeLGAN_with_perceptual_loss | Deep-Exemplar-based-Video-Colorization | |
|---|---|---|
| 1 | 4 | |
| 3 | 330 | |
| - | - | |
| 0.0 | 0.0 | |
| over 3 years ago | over 1 year ago | |
| Python | Python | |
| - | MIT License |
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TraVeLGAN_with_perceptual_loss
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Style Transfer -- presented on GTC 2017, source code available?
I recommend this: https://github.com/richardoey/TraVeLGAN_with_perceptual_loss
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.
What are some alternatives?
stylegan-encoder - StyleGAN Encoder - converts real images to latent space
CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
Few-Shot-Patch-Based-Training - The official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training
image_edit - Demos of neural image editing
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.
OASIS - Official implementation of the paper "You Only Need Adversarial Supervision for Semantic Image Synthesis" (ICLR 2021)
HyperGAN - Composable GAN framework with api and user interface
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”.
esrgan - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution
Deep-Exemplar-based-Video-Colo
StyleSwin - [CVPR 2022] StyleSwin: Transformer-based GAN for High-resolution Image Generation