haoyang-219 Goto Github PK

3dcommoncorruptions

3D Common Corruptions and Data Augmentation, CVPR 2022 [Oral]

a2snn

Panagiotis Eustratiadis and Henry Gouk and Da Li and Timothy M. Hospedales. "A Stochastic Neural Network for Attack-Agnostic Adversarial Robustness". CoRR abs/2010.08852. (2020).

activelearning-sdm

Implementation of CVPR 2022 paper "Learning Distinctive Margin toward Active Domain Adaptation”

adacontrast

Official repository of CVPR '22 paper "Contrastive Test-Time Adaptation"

adversarial-attacks-pytorch

PyTorch implementation of adversarial attacks.

adversarial-contrastive-learning

[NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang

adversarial-distributional-training

Adversarial Distributional Training (NeurIPS 2020)

angular-penalty-softmax-losses-pytorch

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

ares

A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

arm

at_he

auto-attack

Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

awesome-diffusion-models

A collection of resources and papers on Diffusion Models

awesome-domain-adaptation

A collection of AWESOME things about domian adaptation

awesome-fas

Paper collection of about the face anti-spoofing

awesome-graph-ood

Papers about out-of-distribution generalization on graphs.

balancedmse

[CVPR 2022 Oral] Balanced MSE for Imbalanced Visual Regression https://arxiv.org/abs/2203.16427

bayesiandefense

Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network

benchmark-tta

bfa

Pytorch implementation of Bit-Flip based adversarial weight Attack (BFA)

boundary_thickness

[NeurIPS 2020] code for "Boundary thickness and robustness in learning models"

cagcn

Source code of NeurIPS 2021 Paper ''Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration''

cas_iclr2021

cd-vae

[NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"

cdcn

Central Difference Convolutional Networks (CVPR'20)

cflp

Author: Tong Zhao ([email protected]). ICML 2022. Learning from Counterfactual Links for Link Prediction

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

cotta

[CVPR22] CoTTA Code for our CVPR 2022 paper Continual Test-Time Domain Adaptation

cvpr2022-papers-with-code

CVPR 2022 论文和开源项目合集

cvpr_2019_pni

pytorch implementation of Parametric Noise Injection for adversarial defense