Official PyTorch implementation of the paper "Graph-based Generative Face Anonymisation with Pose Preservation" in ICIAP 2021

Related tags

Deep Learninganonygan
Overview

License CC BY-NC-SA 4.0 Python 3.6 Packagist

Contents

AnonyGAN

| Paper |
Graph-based Generative Face Anonymisation with Pose Preservation
Nicola Dall'Asen12, Yiming Wang3, Hao Tang4, Luca Zanella3, Elisa Ricci23.
1University of Pisa, Italy, 2University of Trento, Italy, 3Fondazione Bruno Kessler, Italy, 4ETH Zürich, Switzerland.
In ICIAP 2021.
The repository offers the official implementation of our paper in PyTorch.

Installation

Clone this repo.

git clone [email protected]:Fodark/anonygan.git
cd anonygan/

Needed libraries are provided in the requirements.txt file.

pip install -r requirements.txt should suffice.

Dataset Preparation

  • Download aligned CelebA here
  • Extract aligned version
  • Compute landmarks and mask with the code provided in preparation (modify paths accordingly)

Generating Images Using Pretrained Model

  • Download pretrained model here
  • Place it in ckpts/anonygan.ckpt
  • Preprocess your images with the files in preparation
  • Prepare a .csv files with columns [from, to] with condition and source images names
  • Run test.sh modifying paths accordingly

Train and Test New Models

  • Same as using the pretrained model, for training modify train.sh accordingly

Evaluation

evaluation/automatic_evaluation is the entry point, modify paths accordingly

Acknowledgments

Graph reasoning inspired by BiGraphGAN

Citation

If you use this code for your research, please consider giving a star and citing our paper!

@inproceedings{dallasen2021anonygan,
  title={Graph-based Generative Face Anonymisation with Pose Preservation},
  author={Dall'Asen, Nicola and Wang, Yiming and Tang, Hao and Zanella, Luca and Ricci, Elisa},
  booktitle={International Conference on Image analysis and Processing},
  year={2021}
}

Contributions

If you have any questions/comments/bug reports, feel free to open a github issue or pull a request or e-mail to the author Nicola Dall'Asen ([email protected]).

Owner
Nicola Dall'Asen
AI PhD student @ University of Pisa and Trento, Italy.
Nicola Dall'Asen
rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle.

rastrainer rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle. UI TODO Init UI. Add Block. Add l

deepbands 5 Mar 04, 2022
Self-Supervised Contrastive Learning of Music Spectrograms

Self-Supervised Music Analysis Self-Supervised Contrastive Learning of Music Spectrograms Dataset Songs on the Billboard Year End Hot 100 were collect

27 Dec 10, 2022
This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021.

inverse_attention This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021. Le

Firas Laakom 5 Jul 08, 2022
⚓ Eurybia monitor model drift over time and securize model deployment with data validation

View Demo · Documentation · Medium article 🔍 Overview Eurybia is a Python library which aims to help in : Detecting data drift and model drift Valida

MAIF 172 Dec 27, 2022
A Fast Monotone Rotating Shallow Water model

pyRSW A Fast Monotone Rotating Shallow Water model How fast? As fast as a sustained 2 Gflop/s per core on a 2.5 GHz cpu (or 2048 Gflop/s with 1024 cor

Guillaume Roullet 13 Sep 28, 2022
Deep-learning X-Ray Micro-CT image enhancement, pore-network modelling and continuum modelling

EDSR modelling A Github repository for deep-learning image enhancement, pore-network and continuum modelling from X-Ray Micro-CT images. The repositor

Samuel Jackson 7 Nov 03, 2022
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in

Oliver Hahn 1 Jan 26, 2022
Trax — Deep Learning with Clear Code and Speed

Trax — Deep Learning with Clear Code and Speed Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively us

Google 7.3k Dec 26, 2022
PyTorch code for: Learning to Generate Grounded Visual Captions without Localization Supervision

Learning to Generate Grounded Visual Captions without Localization Supervision This is the PyTorch implementation of our paper: Learning to Generate G

Chih-Yao Ma 41 Nov 17, 2022
Implementation of MA-Trace - a general-purpose multi-agent RL algorithm for cooperative environments.

Off-Policy Correction For Multi-Agent Reinforcement Learning This repository is the official implementation of Off-Policy Correction For Multi-Agent R

4 Aug 18, 2022
"NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search".

NAS-Bench-301 This repository containts code for the paper: "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search". The

AutoML-Freiburg-Hannover 57 Nov 30, 2022
Discord bot-CTFD-Thread-Parser - Discord bot CTFD-Thread-Parser

Discord bot CTFD-Thread-Parser Description: This tools is used to create automat

15 Mar 22, 2022
PyTorch implementation of "Learn to Dance with AIST++: Music Conditioned 3D Dance Generation."

Learn to Dance with AIST++: Music Conditioned 3D Dance Generation. Installation pip install -r requirements.txt Prepare Dataset bash data/scripts/pre

Zj Li 8 Sep 07, 2021
Given a 2D triangle mesh, we could randomly generate cloud points that fill in the triangle mesh

generate_cloud_points Given a 2D triangle mesh, we could randomly generate cloud points that fill in the triangle mesh. Run python disp_mesh.py Or you

Peng Yu 2 Dec 24, 2021
A dual benchmarking study of visual forgery and visual forensics techniques

A dual benchmarking study of facial forgery and facial forensics In recent years, visual forgery has reached a level of sophistication that humans can

8 Jul 06, 2022
Use .csv files to record, play and evaluate motion capture data.

Purpose These scripts allow you to record mocap data to, and play from .csv files. This approach facilitates parsing of body movement data in statisti

21 Dec 12, 2022
The FIRST GANs-based omics-to-omics translation framework

OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi

Xiaoyu Zhang 6 Dec 14, 2022
Code for the paper "Query Embedding on Hyper-relational Knowledge Graphs"

Query Embedding on Hyper-Relational Knowledge Graphs This repository contains the code used for the experiments in the paper Query Embedding on Hyper-

DimitrisAlivas 19 Jul 26, 2022
EsViT: Efficient self-supervised Vision Transformers

Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect

Microsoft 352 Dec 25, 2022
Customer Segmentation using RFM

Customer-Segmentation-using-RFM İş Problemi Bir e-ticaret şirketi müşterilerini segmentlere ayırıp bu segmentlere göre pazarlama stratejileri belirlem

Nazli Sener 7 Dec 26, 2021