PyTorch implementation of neural style transfer algorithm
Pytorch implementation from scratch of [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Huang+, ICCV2017]]
Pytorch implementation of Noisy Student Training for Automatic Speech Recognition and Automatic Pronunciation Error Detection problem
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 (NST) refers to a class of software algorithms that manipulate digital images, or videos, in order to adopt the appearance or visual style of another image. NST algorithms are characterized by their use of deep neural networks for the sake of image transformation.
A bot for Telegram that can transfer style from one image to another
This project focuses on Neural Style Transfer (NST), a technique that applies the style of one image to the content of another image, creating a new, stylized image. NST leverages deep learning models, particularly Convolutional Neural Networks (CNNs), to extract and combine the content and style features of images.
NST algorithm that manages images or videos, to transfer the visual style of another image.
Reproduction of Neural Style Transfer
A simple and minimalistic PyTorch implementation of "A Neural Algorithm of Artistic Style" by Gatys et. al (2015) 🏞
🎨 Implementation of Fast Neural Style Transfer proposed by Justin Johnson et al. in the paper Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Convolutional Neural Network and Neural Style Transfer from Scratch
Implement the neural style transfer algorithm to generate novel artistic images using foundational layers of CNNs (pooling, convolutions) and to stack them properly in a deep network to solve multi-class image classification problems. Creating digital art using Neural Network based Style Transfer.
Telegram Bot @stylizer_bot providing image style transfer using NST & CycleGAN
Algorithm practice exercises using OpenCV
Configuration tree for the Modderation modpack series
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