neural-style-transfer VS image-super-resolution

Compare neural-style-transfer vs image-super-resolution and see what are their differences.

neural-style-transfer

:paintbrush: This repository contains, well-structured Python library and runnable fully prepared Python notebook of the "Neural Style Transfer" algorithm (by egesabanci)
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neural-style-transfer image-super-resolution
1 19
1 4,459
- 1.0%
3.6 0.0
almost 3 years ago 16 days ago
Jupyter Notebook Python
MIT License Apache License 2.0
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neural-style-transfer

Posts with mentions or reviews of neural-style-transfer. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning neural-style-transfer yet.
Tracking mentions began in Dec 2020.

image-super-resolution

Posts with mentions or reviews of image-super-resolution. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-15.

What are some alternatives?

When comparing neural-style-transfer and image-super-resolution you can also consider the following projects:

SwinIR - SwinIR: Image Restoration Using Swin Transformer (official repository)

VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

video2x - A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley II, 2018.

DeepCreamPy - Decensoring Hentai with Deep Neural Networks

MAX-Image-Resolution-Enhancer - Upscale an image by a factor of 4, while generating photo-realistic details.

waifu2x - Image Super-Resolution for Anime-Style Art

fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:

3d-photo-inpainting - [CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting

rust-numpy - PyO3-based Rust bindings of the NumPy C-API

EGVSR - Efficient & Generic Video Super-Resolution

imagededup - 😎 Finding duplicate images made easy!

EDSR_Tensorflow - TensorFlow implementation of 'Enhanced Deep Residual Networks for Single Image Super-Resolution'.