LPIPS metric. pip install lpips
-
Updated
Jul 2, 2024 - Python
LPIPS metric. pip install lpips
StyleGAN Encoder - converts real images to latent space
StyleGAN Encoder - converts real images to latent space
Single Image Reflection Separation with Perceptual Losses
ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks, published in ECCV 2018) implemented in Tensorflow 2.0+. This is an unofficial implementation. With Colab.
StarNet
[ACM MM 20 Oral] PyTorch implementation of Self-supervised Dance Video Synthesis Conditioned on Music
Low-dose CT via Transfer Learning from a 2D Trained Network, In IEEE TMI 2018
Generative Adversarial Network for single image super-resolution in high content screening microscopy images
PyTorch implementation of the Perceptual Evaluation of Speech Quality for wideband audio
A VGG-based perceptual loss function for PyTorch.
A perceptual weighting filter loss for DNN training in speech enhancement
implement Deep Feature Consisten Variational Autoencoder in Tensorflow
Comparing different similarity functions for reconstruction of image on CycleGAN. (https://tandon-a.github.io/CycleGAN_ssim/) Training cycleGAN with different loss functions to improve visual quality of produced images
Experiments with perceptual loss and autoencoders.
Implementation of VAE and Style-GAN Architecture Achieving State of the Art Reconstruction
Pytorch Implementation of Hou, Shen, Sun, Qiu, "Deep Feature Consistent Variational Autoencoder", 2016
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
Add a description, image, and links to the perceptual-losses topic page so that developers can more easily learn about it.
To associate your repository with the perceptual-losses topic, visit your repo's landing page and select "manage topics."