interactive-deep-colorization VS Deep-Exemplar-based-Video-Colorization

Compare interactive-deep-colorization vs Deep-Exemplar-based-Video-Colorization and see what are their differences.

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interactive-deep-colorization Deep-Exemplar-based-Video-Colorization
1 4
2,672 330
- -
0.0 0.0
almost 2 years ago over 1 year ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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interactive-deep-colorization

Posts with mentions or reviews of interactive-deep-colorization. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-22.

Deep-Exemplar-based-Video-Colorization

Posts with mentions or reviews of Deep-Exemplar-based-Video-Colorization. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-19.

What are some alternatives?

When comparing interactive-deep-colorization and Deep-Exemplar-based-Video-Colorization you can also consider the following projects:

DeOldify - A Deep Learning based project for colorizing and restoring old images (and video!)

CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

arXiv2021-RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation [Moved to: https://github.com/hzwer/ECCV2022-RIFE]

Few-Shot-Patch-Based-Training - The official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training

colorization - Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.

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.

Awesome-Image-Colorization - :books: A collection of Deep Learning based Image Colorization and Video Colorization papers.

OASIS - Official implementation of the paper "You Only Need Adversarial Supervision for Semantic Image Synthesis" (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.

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