InterfaceGAN++: Exploring the limits of InterfaceGAN

Overview

InterfaceGAN++: Exploring the limits of InterfaceGAN

Authors: Apavou Clément & Belkada Younes

Python 3.8 pytorch 1.10.2 sklearn 0.21.2

Open In Colab

From left to right - Images generated using styleGAN and the boundaries Bald, Blond, Heavy_Makeup, Gray_Hair

This the the repository to a project related to the Introduction to Numerical Imaging (i.e, Introduction à l'Imagerie Numérique in French), given by the MVA Masters program at ENS-Paris Saclay. The project and repository is based on the work from Shen et al., and fully supports their codebase. You can refer to the original README) to reproduce their results.

Introduction

In this repository, we propose an approach, termed as InterFaceGAN++, for semantic face editing based on the work from Shen et al. Specifically, we leverage the ideas from the previous work, by applying the method for new face attributes, and also for StyleGAN3. We qualitatively explain that moving the latent vector toward the trained boundaries leads in many cases to keeping the semantic information of the generated images (by preserving its local structure) and modify the desired attribute, thus helps to demonstrate the disentangled property of the styleGANs.

🔥 Additional features

  • Supports StyleGAN2 & StyleGAN3 on the classic attributes
  • New attributes (Bald, Gray hair, Blond hair, Earings, ...) for:
    • StyleGAN
    • StyleGAN2
    • StyleGAN3
  • Supports face generation using StyleGAN3 & StyleGAN2

The list of new features can be found on our attributes detection classifier repository

🔨 Training an attribute detection classifier

We use a ViT-base model to train an attribute detection classifier, please refer to our classification code if you want to test it for new models. Once you retrieve the trained SVM from this repo, you can directly move them in this repo and use them.

Generate images using StyleGAN & StyleGAN2 & StyleGAN3

We did not changed anything to the structure of the old repository, please refer to the previous README. For StyleGAN

🎥 Get the pretrained StyleGAN

We use the styleGAN trained on ffhq for our experiments, if you want to reproduce them, run:

wget -P interfacegan/models/pretrain https://www.dropbox.com/s/qyv37eaobnow7fu/stylegan_ffhq.pth

🎥 Get the pretrained StyleGAN2

We use the styleGAN2 trained on ffhq for our experiments, if you want to reproduce them, run:

wget -P models/pretrain https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhq-1024x1024.pkl 

🎥 Get the pretrained StyleGAN3

We use the styleGAN3 trained on ffhq for our experiments, if you want to reproduce them, run:

wget -P models/pretrain https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-ffhq-1024x1024.pkl 

The pretrained model should be copied at models/pretrain. If not, move the pretrained model file at this directory.

🎨 Run the generation script

If you want to generate 10 images using styleGAN3 downloaded before, run:

python generate_data.py -m stylegan3_ffhq -o output_stylegan3 -n 10

The arguments are exactly the same as the arguments from the original repository, the code supports the flag -m stylegan3_ffhq for styleGAN3 and -m stylegan3_ffhq for styleGAN2.

✏️ Edit generated images

You can edit the generated images using our trained boundaries! Depending on the generator you want to use, make sure that you have downloaded the right model and put them into models/pretrain.

Examples

Please refer to our interactive google colab notebook to play with our models by clicking the following badge:

Open In Colab

StyleGAN

Example of generated images using StyleGAN and moving the images towards the direction of the attribute grey hair:

original images generated with StyleGAN

grey hair version of the images generated with StyleGAN

StyleGAN2

Example of generated images using StyleGAN2 and moving the images towards the opposite direction of the attribute young:

original images generated with StyleGAN2

non young version of the images generated with StyleGAN2

StyleGAN3

Example of generated images using StyleGAN3 and moving the images towards the attribute beard:

Owner
Younes Belkada
MSc Student in Mathematics - Machine Learning - Perception | M2 MVA @ ENS Paris-Saclay
Younes Belkada
Cowsay - A rewrite of cowsay in python

Python Cowsay A rewrite of cowsay in python. Allows for parsing of existing .cow

James Ansley 3 Jun 27, 2022
Coded illumination for improved lensless imaging

CodedCam Coded Illumination for Improved Lensless Imaging Paper | Supplementary results | Data and Code are available. Coded illumination for improved

Computational Sensing and Information Processing Lab 1 Nov 29, 2021
A Partition Filter Network for Joint Entity and Relation Extraction EMNLP 2021

EMNLP 2021 - A Partition Filter Network for Joint Entity and Relation Extraction

zhy 127 Jan 04, 2023
🌈 PyTorch Implementation for EMNLP'21 Findings "Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer"

SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P

Gi-Cheon Kang 9 Jul 05, 2022
Dataset VSD4K includes 6 popular categories: game, sport, dance, vlog, interview and city.

CaFM-pytorch ICCV ACCEPT Introduction of dataset VSD4K Our dataset VSD4K includes 6 popular categories: game, sport, dance, vlog, interview and city.

96 Jul 05, 2022
Deep Learning agent of Starcraft2, similar to AlphaStar of DeepMind except size of network.

Introduction This repository is for Deep Learning agent of Starcraft2. It is very similar to AlphaStar of DeepMind except size of network. I only test

Dohyeong Kim 136 Jan 04, 2023
Discord bot for notifying on github events

Git-Observer Discord bot for notifying on github events ⚠️ This bot is meant to write messages to only one channel (implementing this for multiple pro

ilu_vatar_ 0 Apr 19, 2022
VGGFace2-HQ - A high resolution face dataset for face editing purpose

The first open source high resolution dataset for face swapping!!! A high resolution version of VGGFace2 for academic face editing purpose

Naiyuan Liu 232 Dec 29, 2022
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.

Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.

Sidd Karamcheti 50 Nov 16, 2022
Generate pixel-style avatars with python.

face2pixel Generate pixel-style avatars with python. Run: Clone the project: git clone https://github.com/theodorecooper/face2pixel install requiremen

Theodore Cooper 2 May 11, 2022
Federated_learning codes used for the the paper "Evaluation of Federated Learning Aggregation Algorithms" and "A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison"

Federated Distance (FedDist) This is the code accompanying the Percom2021 paper "A Federated Learning Aggregation Algorithm for Pervasive Computing: E

GETALP 8 Jan 03, 2023
Improving Query Representations for DenseRetrieval with Pseudo Relevance Feedback:A Reproducibility Study.

APR The repo for the paper Improving Query Representations for DenseRetrieval with Pseudo Relevance Feedback:A Reproducibility Study. Environment setu

ielab 8 Nov 26, 2022
AI Virtual Calculator: This is a simple virtual calculator based on Artificial intelligence.

AI Virtual Calculator: This is a simple virtual calculator that works with gestures using OpenCV. We will use our hand in the air to click on the calc

Md. Rakibul Islam 1 Jan 13, 2022
InvTorch: memory-efficient models with invertible functions

InvTorch: Memory-Efficient Invertible Functions This module extends the functionality of torch.utils.checkpoint.checkpoint to work with invertible fun

Modar M. Alfadly 12 May 12, 2022
CNN designed for pansharpening

PROGRESSIVE BAND-SEPARATED CONVOLUTIONAL NEURAL NETWORK FOR MULTISPECTRAL PANSHARPENING This repository contains main code for the paper PROGRESSIVE B

SerendipitysX 3 Dec 29, 2021
PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features

PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features Overview This repository is the Pytorch implementation of PRIN/SPRIN: On Extracting P

Yang You 17 Mar 02, 2022
AdaFocus (ICCV 2021) Adaptive Focus for Efficient Video Recognition

AdaFocus (ICCV 2021) This repo contains the official code and pre-trained models for AdaFocus. Adaptive Focus for Efficient Video Recognition Referenc

Rainforest Wang 115 Dec 21, 2022
Config files for my GitHub profile.

Canalyst Candas Data Science Library Name Canalyst Candas Description Built by a former PM / analyst to give anyone with a little bit of Python knowle

Canalyst Candas 13 Jun 24, 2022
Neural network-based build time estimation for additive manufacturing

Neural network-based build time estimation for additive manufacturing Oh, Y., Sharp, M., Sprock, T., & Kwon, S. (2021). Neural network-based build tim

Yosep 1 Nov 15, 2021
[NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning

SoCo [NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning By Fangyun Wei*, Yue Gao*, Zhirong Wu, Han Hu,

Yue Gao 139 Dec 14, 2022