Official Code for AdvRush: Searching for Adversarially Robust Neural Architectures (ICCV '21)

Last update: Dec 10, 2022

Related tags

Overview

AdvRush

Official Code for AdvRush: Searching for Adversarially Robust Neural Architectures (ICCV '21)

Environmental Set-up

Python == 3.6.12, PyTorch == 1.2.0, torchvision == 0.4.0

AdvRush Search Process

cd advrush && python train_search.py --batch_size 32 --gpu 0 --epochs 60 --a_gamma 0.01 --a_warmup_epochs 0 --w_warmup_epochs 60 --loss_hessian loss_cure

Adversarial Training

cd advrush && python adv_train.py --batch_size 64 --gpu 0 --epochs 200 --adv_loss pgd --arch ADVRUSH

Evaluation under PGD Attack

Prior to the evaluation process, add all necessary checkpoint files (preferably in the form of .pth.tar) to the /eval/checkpoints folder. To conduct white-box attacks,

cd eval &&
python pgd_attack.py --white-box-attack True --test-batch-size 10 --arch [arch_name] --checkpoint [./checkpoints/file_name.pth.tar] --data_type [cifar10/svhn]

To conduct black-box attacks,

cd eval &&
python pgd_attack.py --test-batch-size 10 --target_arch [target_arch] --target_checkpoint [./checkpoints/target_file.pth.tar] --source_arch [source_arch] --source_checkpoint [./checkpoints/source_file.pth.tar] --data_type cifar10

References

DARTS: Differentiable Architecture Search [ICLR '19] code paper

Robustness via Curvature Regularization, and Vice Versa [CVPR '19] code paper

Tradeoff-inspired Adversarial Defense via Surrogate-loss Minimization [ICML '19] code paper

Official Code for AdvRush: Searching for Adversarially Robust Neural Architectures (ICCV '21)

Related tags

Overview

AdvRush

Environmental Set-up

AdvRush Search Process

Adversarial Training

Evaluation under PGD Attack

References

Owner

QueryDet: Cascaded Sparse Query for Accelerating High-Resolution SmallObject Detection

RE3: State Entropy Maximization with Random Encoders for Efficient Exploration

Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification

Combinatorial model of ligand-receptor binding

This repository provides an efficient PyTorch-based library for training deep models.

A Keras implementation of CapsNet in the paper: Sara Sabour, Nicholas Frosst, Geoffrey E Hinton. Dynamic Routing Between Capsules

Library for 8-bit optimizers and quantization routines.

Pytorch code for our paper "Feedback Network for Image Super-Resolution" (CVPR2019)

Rank1 Conversation Emotion Detection Task

Neural Scene Flow Prior (NeurIPS 2021 spotlight)

공공장소에서 눈만 돌리면 CCTV가 보인다는 말이 과언이 아닐 정도로 CCTV가 우리 생활에 깊숙이 자리 잡았습니다.

Stacked Generative Adversarial Networks

Solve a Rubiks Cube using Python Opencv and Kociemba module

Implementation for the IJCAI2021 work "Beyond the Spectrum: Detecting Deepfakes via Re-synthesis"

Efficient semidefinite bounds for multi-label discrete graphical models.

Final project for machine learning (CSC 590). Detection of hepatitis C and progression through blood samples.

Python implementation of Wu et al (2018)'s registration fusion

🧮 Matrix Factorization for Collaborative Filtering is just Solving an Adjoint Latent Dirichlet Allocation Model after All

PySOT - SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.

A high-level Python library for Quantum Natural Language Processing