GitHub - harrywuhust2022/CR-GAT-RT: Certified Radius-Guided Attacks and Robustness Training against Semantic Segmentation

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Certified Radius-Guided Attacks and Robustness Training against Semantic Segmentation

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Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
Cityscape		Cityscape
VOC2012		VOC2012
base		base
dataloaders		dataloaders
models		models
utils		utils
attack.py		attack.py
configcit_deep.json		configcit_deep.json
configcit_fcn.json		configcit_fcn.json
configcit_psp.json		configcit_psp.json
configcit_uper.json		configcit_uper.json
configvoc_deep.json		configvoc_deep.json
configvoc_fcn.json		configvoc_fcn.json
configvoc_psp.json		configvoc_psp.json
configvoc_uper.json		configvoc_uper.json
readme.txt		readme.txt
test.py		test.py
testdefense.py		testdefense.py
tools.py		tools.py
train.py		train.py
trainer.py		trainer.py

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# Certified Radius-Guided Attacks and Efficient
Robustness Training against Deep Neural Networks, IEEE Security & Privacy 2021
\
Wenjie Qu*, Qiming Wu*, Pan Zhou and Binghui Wang


## how to train :
* python train.py --config=configvoc_fcn.json

## how to test(attack):
* python3 test.py --binname=fcn_voc.pth --config=configvoc_fcn.json


## how to test(defense):
* python3 testdefense.py --binname=fcn_voc_def.pth --config=configvoc_fcn.json