zjfheart

stablediffusion

High-Resolution Image Synthesis with Latent Diffusion Models

TaskMatrix

pytorch-image-models

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

MiniGPT-4

Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)

awesome-english-ebooks

经济学人(含音频)、纽约客、卫报、连线、大西洋月刊等英语杂志免费下载,支持epub、mobi、pdf格式, 每周更新

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

AudioGPT

AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head

CnOCR

CnOCR: Awesome Chinese/English OCR Python toolkits based on PyTorch. It comes with 20+ well-trained models for different application scenarios and can be used directly after installation. 【基于 PyTorch/MXNet 的中文/英文 OCR Python 包。】

Friendly-Adversarial-Training

Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)

system-fonts

Which fonts can I use?

Geometry-aware-Instance-reweighted-Adversarial-Training

the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral

Defend_MI

Bilateral Dependency Optimization: Defending Against Model-inversion Attacks

CIFS

CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection

SAMMD

This is the source code for Maximum Mean Discrepancy Test is Aware of Adversarial Attacks (ICML2021).

IAD

[ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers

ATCL

[NeurIPS 2022] "Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks"

RobustSSL_Benchmark

Benchmark of robust self-supervised learning (RobustSSL) methods & Code for AutoLoRa (ICLR 2024).

NoiLIn

The code for NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels (TMLR 22 accept)

Enhancing_ACL_via_AIR

Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization (NeurIPS 2023)

StablePrivateLoRA

BadLabels

Challenging label noise called BadLabel; Robust label-noise learning called Robust DivideMix

dsnet

Code for ICML'21 paper Learning Diverse-Structured Networks for Adversarial Robustness

Efficient_ACL_via_RCS

Efficient Adversarial Contrastive Learning via Robustness-aware Coreset Selection (NeurIPS 2023 Spotlight)

ObsAtk

Implementation of "Towards Adversarially Robust Deep Image Denoising" (IJCAI 2022)

taskaugment

Robust-TST

Adversarial Attacks and Defense for Non-Parametric Two-Sample Tests (ICML 2022)

trustMLresearch.github.io

Website

Poison-adv-training

Poisoning attack methods against adversarial training algorithms

wsl-workshop.github.io

Weakly supervised learning workshops

synergy-of-experts