yanzhaowu / bmvc2018r-ap Goto Github PK

DenseFoolbox is a python repository for white-box attacking object detectors, instance segmentation. This repository is a simple implementation of our paper Robust Adversarial Perturbation on Deep Proposal-based Models, BMVC2018.

1. Overview
2. Requirements
3. Demo

We target Region Proposal Network (RPN) as the bottleneck of Deep-proposal based networks. The detections can be disrupted by breaking object proposal generation. To do so, we disturb the predicted class score as well as offset regression of object proposals.

• Pytorch 0.4.0
• Ubuntu 16.04
• CUDA 8.0
• Python 2.7
• opencv3

1. We use Faster-RCNN detector based on pytorch framework pytorch-faster-rcnn. We make modifications to this repository which can be downloaded here.
2. Unzip the repository to object_detectors.
3. Look into attack_wrapper/object_detectors_v2 and run run.py.

   python run.py \
   --net=faster-rcnn \  # faster-rcnn or ssd (update later)
   --base=vgg16 \
   --data_dir=demo/ \
   --res_dir=res/
   

Update later

If you find this implementation helpful, please cite:

@inproceedings{li2018rap,
author={Li, Yuezun and Tian, Daniel and Chang, Mingching and Bian, Xiao and Lyu, Siwei},
title={Robust Adversarial Perturbation on Deep Proposal-based Models},
booktitle={BMVC},
year={2018}}