yzx1213's Stars
JanSky520/CS_Introduction
《计算机科学导论》课后习题答案
fuhmmin/it-ebooks-cn
计算机电子书pdf整理
LC044/WeChatMsg
提取微信聊天记录,将其导出成HTML、Word、Excel文档永久保存,对聊天记录进行分析生成年度聊天报告,用聊天数据训练专属于个人的AI聊天助手
OOrangeeee/Message_Analysis
用于进行微信年终分析总结,包括出现的词语频率,emoji频率,热度,语句分析等等。
windingwind/zotero-pdf-translate
Translate PDF, EPub, webpage, metadata, annotations, notes to the target language. Support 20+ translate services.
neuralcollapse/neuralcollapse
Code reproducing Neural Collapse phenomenon on MSE and cross-entropy loss
sjtug/SJTUThesis
上海交通大学 LaTeX 论文模板 | Shanghai Jiao Tong University LaTeX Thesis Template
val-iisc/GD-UAP
Generalized Data-free Universal Adversarial Perturbations
hyz-xmaster/swa_object_detection
SWA Object Detection
bethgelab/imagecorruptions
Python package to corrupt arbitrary images.
naoto0804/pytorch-AdaIN
Unofficial pytorch implementation of 'Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization' [Huang+, ICCV2017]
hendrycks/robustness
Corruption and Perturbation Robustness (ICLR 2019)
krumo/Domain-Adaptive-Faster-RCNN-PyTorch
Domain Adaptive Faster R-CNN in PyTorch
rbgirshick/py-faster-rcnn
Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version
Feobi1999/TDD
open-mmlab/mmdetection
OpenMMLab Detection Toolbox and Benchmark
psyker-team/mist
Watermark you artworks to stay away from unauthorized diffusion style mimicry!
nblt/TWA
[ICLR 2023] Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions
VICO-UoE/DatasetCondensation
Dataset Condensation (ICLR21 and ICML21)
yuchenlin/rebiber
A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).
Lyn-L/PDUA
The Project of Our ICCV Paper
BardOfCodes/universal_pytorch
Pytorch implementation of Universal Adverserial Perturbation and Fast Feature Fool
cihangxie/DI-2-FGSM
Improving Transferability of Adversarial Examples with Input Diversity
kai-wen-yang/CD-VAE
[NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"
xherdan76/A-Unified-Approach-to-Interpreting-and-Boosting-Adversarial-Transferability
A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)
qizhangli/linbp-attack
Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.
ZhengyuZhao/Targeted-Transfer
Simple yet effective targeted transferable attack (NeurIPS 2021)
CUAI/Intermediate-Level-Attack
[ICCV 2019] Enhancing Adversarial Example Transferability with an Intermediate Level Attack (https://arxiv.org/abs/1907.10823)
JHL-HUST/VT
Enhancing the Transferability of Adversarial Attacks through Variance Tuning
hcguoO0/FIA
code for "Feature Importance-aware Transferable Adversarial Attacks"