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DartBlur

Privacy Preservation with Detection Artifact Suppression

Paper | Supplemental | Video

Baowei Jiang*, Bing Bai*, Haozhe Lin*, Yu Wang, Yuchen Guo, Lu Fang

License: MIT

Table of Contents

Overview

overview

Data Preparation

Download WIDER FACE Dataset

You can download images and annotations from website, and unzip files to data/widerface/.

[Expected directory structure of WIDERFACE (click to expand)]
./data/widerface
└───train
│   └───images
│   |   └───0--Parade
│   |       │   0_Parade_marchingband_1_5.jpg
│   |       │   ...
│   |   └───1--Handshaking
│   |       │   1_Handshaking_Handshaking_1_42.jpg
│   |       │   ...
|   |   ...
└───val
│   └───images
│   |   └───0--Parade
│   |       │   0_Parade_marchingband_1_20.jpg
│   |       │   ...
│   |   └───1--Handshaking
│   |       │   1_Handshaking_Handshaking_1_35.jpg
│   |       │   ...
|   |   ...
└───wider_face_split
|   └───wider_face_train_bbx_gt.txt
|   └───wider_face_val_bbx_gt.txt
|   └───...

Download WIDER FACE labels

You need download labels file from RetinaFace Organise the dataset directory as follows:

[Expected directory structure of WIDERFACE (click to expand)]
./data/widerface
└───train
│   └───images
│   └───label.txt
└───val
│   └───images
│   └───label.txt

Data pre-processing: Gaussian Blur

python gaussblur.py

Dartblur Images

python dartblur.py

Training

dependency installation

(Ubuntu/Win10 3090Ti cuda11.8)
conda create -n dartblur python=3.8
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
pip install -r requirements.txt

start training

python train.py

Reference

https://github.com/bubbliiiing/retinaface-pytorch

Citation

@inproceedings{jiang2023dartblur,
title={DartBlur: Privacy Preservation With Detection Artifact Suppression},
author={Jiang, Baowei and Bai, Bing and Lin, Haozhe and Wang, Yu and Guo, Yuchen and Fang, Lu},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={16479--16488},
year={2023}
}

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