Demake-up Filter Use Unet model, Resnet50 Pretrained

Generate data, PSNR, Perceptual Loss, Unet

Android librarry (kotlin) : Image (JPEG, BMP) comparison (perceptual hash algorithm)

🎨 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

Final assignment in the NLP course at the Technion (IEM097215). In this assignment we propose a novel architecture to handle both Text-to-Image translation and Image-to-Text translation tasks on paired data, using a unified architecture of transformers and CNNs and enforcing cycle consistency.

This project features an automatic image colorization model utilizing a U-Net architecture combined with perceptual loss for enhanced colorization quality.

Demos of neural image editing

This is a very simplified ipynb code for KupynOrest's Deblur GAN code. DeblurGAN addresses the challenge of end-to-end image deblurring through the use of conditional Generative Adversarial Networks (cGANs).I have used pytorch for this implementation.

single image super resolution

Official implementation of RDST. A residual dense swin transformer for medical image super-resolution

Pytorch implementation of Neural Style Transfer (NST). Reviewing litterature and implementing some ideas.

LPIPS metric on PaddlePaddle. pip install paddle-lpips

Investigation in 4x Super-resolution by Deep Convolutional Neural Networks

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) 🏞

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.

Implementation of the fast neural style transfer algorithm on Keras. Includes Jupyter notebooks, python script and web app.

A no-reference version of HDR-VDP using deep-learning

A deep perceptual metric for 3D point clouds

A Study of Deep Perceptual Metrics for Image quality Assessment

Pytorch Implementation of Hou, Shen, Sun, Qiu, "Deep Feature Consistent Variational Autoencoder", 2016