mabo1215/ppedcrf-sensnet

PPEDCRF: Privacy-Preserving Enhanced Dynamic CRF

PPEDCRF is a framework for location-privacy protection in dashcam videos. It identifies and tracks location-sensitive background regions using a dynamic Conditional Random Field (CRF) and applies calibrated perturbations to these regions while preserving foreground detection and segmentation utility. This repository contains the sensitive-region predictor (SensNet) component of the framework.

• Paper: PPEDCRF: Privacy-Preserving Enhanced Dynamic CRF for Location-Privacy Protection for Sequence Videos with Minimal Detection Degradation
• Code: GitHub Repository

Usage

This model is intended to be used with the official research codebase.

Installation

git clone https://github.com/mabo1215/PPEDCRF.git
cd PPEDCRF
pip install -r src/requirements.txt

Video Protection

To use this pre-trained checkpoint to protect video clips:

python src/main.py --config src/config/config.yaml protect --checkpoint mabo1215/ppedcrf-sensnet

Citation

@article{ma2024ppedcrf,
  title={PPEDCRF: Privacy-Preserving Enhanced Dynamic CRF for Location-Privacy Protection for Sequence Videos with Minimal Detection Degradation},
  author={Ma, Bo and Wu, Jinsong and Yan, Weiqi and Shi, Catherine and Nguyen, Minh},
  journal={arXiv preprint arXiv:2603.01593},
  year={2024}
}