Deep-Exemplar-based-Video-Colorization
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| Deep-Exemplar-based-Video-Colorization | mmagic | |
|---|---|---|
| 4 | 5 | |
| 317 | 6,555 | |
| - | 2.4% | |
| 0.0 | 8.7 | |
| over 1 year ago | about 1 month ago | |
| Python | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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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.
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- More than Editing, Unlock the Magic!
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MMEditing v1.0.0rc4 has been released （including Disco-Diffusion）
Join us to make it better! Try at https://github.com/open-mmlab/mmediting/tree/1.x
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What are some alternatives?
CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
a-PyTorch-Tutorial-to-Super-Resolution - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
Few-Shot-Patch-Based-Training - The official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
OASIS - Official implementation of the paper "You Only Need Adversarial Supervision for Semantic Image Synthesis" (ICLR 2021)
Image-Super-Resolution-via-Iterative-Refinement - Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
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.
Real-ESRGAN-colab - A Real-ESRGAN model trained on a custom dataset
HyperGAN - Composable GAN framework with api and user interface
cnn-watermark-removal - Fully convolutional deep neural network to remove transparent overlays from images
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”.
contrastive-unpaired-translation - Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)