Reconstruction of the original paper on neural style transfer (Gatys et al.). I've additionally included reconstruction scripts which allow you to reconstruct only the content or the style of the image - for better understanding of how NST works.

Reference code for the paper CAMS: Color-Aware Multi-Style Transfer.

Fast Neural Style Transfer implementation using PyTorch > ONNX Inference

A simple and minimalistic implementation of the fast neural style transfer method presented in "Perceptual Losses for Real-Time Style Transfer and Super-Resolution" by Johnson et. al. (2016) 🏞

Neural Style Transfer done from the CLI using a VGG backbone and presented as an MP4.

This is a social volunteering project for implementing neural style transfer algorithm for creating artistic styles with awesome textures to be printed on tees :)

PyTorch implementation of "A Learned Representation For Artistic Style"

Implementation of the neural style transfer paper titled "Image Style Transfer Using Convolutional Neural Networks" using PyTorch.

A simple and minimalistic PyTorch implementation of "A Neural Algorithm of Artistic Style" by Gatys et. al (2015) 🏞

Composable, light-weight style transfer

Implementation of the original paper on neural style transfer from Gatys et al.

Original Implementation of Neural Style Transfer in pytorch. Inspection has been performed into the working of thereof by changing the hyperparameters.

Implementation of Neural Style Transfer based on the original paper by Gatys et al., with adaptations from Deep Learning with Python by François Chollet. This notebook allows you to experiment with style transfer, content reconstruction, and style reconstruction to explore and gain a deeper understanding of how Neural Style Transfer (NST) works.

Reproduction of Neural Style Transfer

Implemented basic deep learning models using PyTorch

Peking University 2023 Fall Computer Vision Course Final Assignment Project

An application that changes the background of a content image.

Neural Style Transfer implemented in PyTorch, featuring a user-friendly Streamlit app for blending content and artistic styles into stunning images.

Pytorch implementation of "Image style transfer using convolutional neural networks", Gatys et al. with an interactive app