426 Repositories
Python adversarial-patches Libraries
🔥3D-RecGAN in Tensorflow (ICCV Workshops 2017)
3D Object Reconstruction from a Single Depth View with Adversarial Learning Bo Yang, Hongkai Wen, Sen Wang, Ronald Clark, Andrew Markham, Niki Trigoni
A repository for the paper "Improved Adversarial Systems for 3D Object Generation and Reconstruction".
Improved Adversarial Systems for 3D Object Generation and Reconstruction: This is a repository for the paper "Improved Adversarial Systems for 3D Obje
Torch implementation of various types of GAN (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN, LSGAN)
gans-collection.torch Torch implementation of various types of GANs (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN). Note that EBGAN and
Tensorflow Implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (ICML 2017 workshop)
tf-SNDCGAN Tensorflow implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (https://www.researchgate.net/publicati
TensorFlow implementation of Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently.
Adversarial Chess TensorFlow implementation of Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently. Requirements To run
Training, generation, and analysis code for Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics
Location-Aware Generative Adversarial Networks (LAGAN) for Physics Synthesis This repository contains all the code used in L. de Oliveira (@lukedeo),
TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"
Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T
A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.
Adversarial Video Generation This project implements a generative adversarial network to predict future frames of video, as detailed in "Deep Multi-Sc
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
SalGAN: Visual Saliency Prediction with Adversarial Networks Junting Pan Cristian Canton Ferrer Kevin McGuinness Noel O'Connor Jordi Torres Elisa Sayr
Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.
cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut
Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
Photo-Realistic-Super-Resoluton Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" [Paper]
[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs
Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
MGANs Training & Testing code (torch), pre-trained models and supplementary materials for "Precomputed Real-Time Texture Synthesis with Markovian Gene
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
CycleGAN PyTorch | project page | paper Torch implementation for learning an image-to-image translation (i.e. pix2pix) without input-output pairs, for
Image-to-image translation with conditional adversarial nets
pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat
Age Progression/Regression by Conditional Adversarial Autoencoder
Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE) TensorFlow implementation of the algorithm in the paper Age Progression/Regre
Image De-raining Using a Conditional Generative Adversarial Network
Image De-raining Using a Conditional Generative Adversarial Network [Paper Link] [Project Page] He Zhang, Vishwanath Sindagi, Vishal M. Patel In this
Fully Convolutional Refined Auto Encoding Generative Adversarial Networks for 3D Multi Object Scenes
Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes This repository contains the source code for Full
3D Generative Adversarial Network
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling This repository contains pre-trained models and sampling
Sketch-Based 3D Exploration with Stacked Generative Adversarial Networks
pix2vox [Demonstration video] Sketch-Based 3D Exploration with Stacked Generative Adversarial Networks. Generated samples Single-category generation M
Generative Adversarial Text-to-Image Synthesis
###Generative Adversarial Text-to-Image Synthesis Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee This is the
Text to image synthesis using thought vectors
Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
StackGAN Pytorch implementation Inception score evaluation StackGAN-v2-pytorch Tensorflow implementation for reproducing main results in the paper Sta
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
Interactive Image Generation via Generative Adversarial Networks
iGAN: Interactive Image Generation via Generative Adversarial Networks Project | Youtube | Paper Recent projects: [pix2pix]: Torch implementation for
A DCGAN to generate anime faces using custom mined dataset
Anime-Face-GAN-Keras A DCGAN to generate anime faces using custom dataset in Keras. Dataset The dataset is created by crawling anime database websites
A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations.
IllustrationGAN A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations. Generated Images
Learning Chinese Character style with conditional GAN
zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(字到字, me
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq
Code and hyperparameters for the paper "Generative Adversarial Networks"
Generative Adversarial Networks This repository contains the code and hyperparameters for the paper: "Generative Adversarial Networks." Ian J. Goodfel
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
Curated list of awesome GAN applications and demo
gans-awesome-applications Curated list of awesome GAN applications and demonstrations. Note: General GAN papers targeting simple image generation such
A list of all named GANs!
The GAN Zoo Every week, new GAN papers are coming out and it's hard to keep track of them all, not to mention the incredibly creative ways in which re
Collection of generative models in Tensorflow
tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th
Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
Pytorch implementation of forward and inverse Haar Wavelets 2D
Pytorch implementation of forward and inverse Haar Wavelets 2D
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa
⚖️🔁🔮🕵️♂️🦹🖼️ Code for *Measuring the Contribution of Multiple Model Representations in Detecting Adversarial Instances* paper.
Measuring the Contribution of Multiple Model Representations in Detecting Adversarial Instances This repository contains the code for Measuring the Co
Generating Band-Limited Adversarial Surfaces Using Neural Networks
Generating Band-Limited Adversarial Surfaces Using Neural Networks This is the official repository of the technical report that was published on arXiv
Improving the robustness and performance of biomedical NLP models through adversarial training
RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s
Chainer Implementation of Semantic Segmentation using Adversarial Networks
Semantic Segmentation using Adversarial Networks Requirements Chainer (1.23.0) Differences Use of FCN-VGG16 instead of Dilated8 as Segmentor. Caution
A graph adversarial learning toolbox based on PyTorch and DGL.
GraphWar: Arms Race in Graph Adversarial Learning NOTE: GraphWar is still in the early stages and the API will likely continue to change. 🚀 Installat
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness Code for Paper "Imbalanced Gradients: A Subtle Cause of Overestimated Adv
FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack
FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack Case study of the FCA. The code can be find in FCA. Cas
The official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness.
This repository is the official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness. Requirements pip install -r requi
Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.
Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu
Code for paper "Role-oriented Network Embedding Based on Adversarial Learning between Higher-order and Local Features"
Role-oriented Network Embedding Based on Adversarial Learning between Higher-order and Local Features Train python main.py --dataset brazil-flights C
Code for "Adversarial attack by dropping information." (ICCV 2021)
AdvDrop Code for "AdvDrop: Adversarial Attack to DNNs by Dropping Information(ICCV 2021)." Human can easily recognize visual objects with lost informa
code for "Feature Importance-aware Transferable Adversarial Attacks"
Feature Importance-aware Attack(FIA) This repository contains the code for the paper: Feature Importance-aware Transferable Adversarial Attacks (ICCV
Code repository for EMNLP 2021 paper 'Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods'
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods This is the code repository to accompany the EMNLP 2021 paper on ad
Adversarial Graph Augmentation to Improve Graph Contrastive Learning
ADGCL : Adversarial Graph Augmentation to Improve Graph Contrastive Learning Introduction This repo contains the Pytorch [1] implementation of Adversa
PyTorch implementation of "PatchGame: Learning to Signal Mid-level Patches in Referential Games" to appear in NeurIPS 2021
PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin
This library is testing the ethics of language models by using natural adversarial texts.
prompt2slip This library is testing the ethics of language models by using natural adversarial texts. This tool allows for short and simple code and v
Official repository for the NeurIPS 2021 paper Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided curriculum Learning Approach
Get Fooled for the Right Reason Official repository for the NeurIPS 2021 paper Get Fooled for the Right Reason: Improving Adversarial Robustness throu
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without
PyTorch implementation of "PatchGame: Learning to Signal Mid-level Patches in Referential Games" to appear in NeurIPS 2021
PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin
Companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsura et al.
META-RS This is the companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsu
Generative Adversarial Networks(GANs)
Generative Adversarial Networks(GANs) Vanilla GAN ClusterGAN Vanilla GAN Model Structure Final Generator Structure A MLP with 2 hidden layers of hidde
Code for "Adversarial Attack Generation Empowered by Min-Max Optimization", NeurIPS 2021
Min-Max Adversarial Attacks [Paper] [arXiv] [Video] [Slide] Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang, Tianyun Zha
Data Poisoning based on Adversarial Attacks using Non-Robust Features
Data Poisoning based on Adversarial Attacks using Non-Robust Features Usage python main.py [-h] [--gpu | -g GPU] [--eps |-e EPSILON] [--pert | -p PER
Enhancing Knowledge Tracing via Adversarial Training
Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification (ACDNE) This is a pytorch implementation of the Adv
Implementation of average- and worst-case robust flatness measures for adversarial training.
Relating Adversarially Robust Generalization to Flat Minima This repository contains code corresponding to the MLSys'21 paper: D. Stutz, M. Hein, B. S
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
Adversarial Robustness with Non-uniform Perturbations
Adversarial Robustness with Non-uniform Perturbations This repository hosts the code to replicate experiments of the paper Adversarial Robustness with
AugMax: Adversarial Composition of Random Augmentations for Robust Training
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
Unofficial implement with paper SpeakerGAN: Speaker identification with conditional generative adversarial network
Introduction This repository is about paper SpeakerGAN , and is unofficially implemented by Mingming Huang ([email protected]), Tiezheng Wang (wtz920729
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"
Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
[NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Code for NeurIPS 2021 paper "Better Safe Than Sorry: Preventing Delu
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t
This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams.
Mutli-agent task allocation This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams. To change
Code for "Generative adversarial networks for reconstructing natural images from brain activity".
Reconstruct handwritten characters from brains using GANs Example code for the paper "Generative adversarial networks for reconstructing natural image
This repository contains all source code, pre-trained models related to the paper "An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator"
An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o
NeurIPS'21: Probabilistic Margins for Instance Reweighting in Adversarial Training (Pytorch implementation).
source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training
Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative adversarial networks (GAN)
Flickr-Faces-HQ Dataset (FFHQ) Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative
Implements the training, testing and editing tools for "Pluralistic Image Completion"
Pluralistic Image Completion ArXiv | Project Page | Online Demo | Video(demo) This repository implements the training, testing and editing tools for "
This repository contains an implementation of ConvMixer for the ICLR 2022 submission "Patches Are All You Need?".
Patches Are All You Need? 🤷 This repository contains an implementation of ConvMixer for the ICLR 2022 submission "Patches Are All You Need?". Code ov
Codebase for Time-series Generative Adversarial Networks (TimeGAN)
Codebase for Time-series Generative Adversarial Networks (TimeGAN)
Pytorch implementation of the paper Time-series Generative Adversarial Networks
TimeGAN-pytorch Pytorch implementation of the paper Time-series Generative Adversarial Networks presented at NeurIPS'19. Jinsung Yoon, Daniel Jarrett
Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks
ForecastingNonverbalSignals This is the implementation for the paper Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative A
3D-aware GANs based on NeRF (arXiv).
CIPS-3D This repository will contain the code of the paper, CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis.
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
This repository contains the code accompanying the paper " FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation" Paper link: R
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
Focal Frequency Loss - Official PyTorch Implementation This repository provides the official PyTorch implementation for the following paper: Focal Fre
CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction. ICCV 2021
crfill Usage | Web App | | Paper | Supplementary Material | More results | code for paper ``CR-Fill: Generative Image Inpainting with Auxiliary Contex
A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.
ARES This repository contains the code for ARES (Adversarial Robustness Evaluation for Safety), a Python library for adversarial machine learning rese
Code for SALT: Stackelberg Adversarial Regularization, EMNLP 2021.
SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R
Python code to generate art with Generative Adversarial Network
GAN_Canvas_Maker Generating Art using Generative Adversarial Network (GAN) Python code to generate art with Generative Adversarial Network: https://to
PyTorch implementation of our method for adversarial attacks and defenses in hyperspectral image classification.
Self-Attention Context Network for Hyperspectral Image Classification PyTorch implementation of our method for adversarial attacks and defenses in hyp
Boosting Adversarial Attacks with Enhanced Momentum (BMVC 2021)
EMI-FGSM This repository contains code to reproduce results from the paper: Boosting Adversarial Attacks with Enhanced Momentum (BMVC 2021) Xiaosen Wa
Implementation of ConvMixer in TensorFlow and Keras
ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in that it operates directly on
Unsupervised Image Generation with Infinite Generative Adversarial Networks
Unsupervised Image Generation with Infinite Generative Adversarial Networks Here is the implementation of MICGANs using DCGAN architecture on MNIST da
A style-based Quantum Generative Adversarial Network
Style-qGAN A style based Quantum Generative Adversarial Network (style-qGAN) model for Monte Carlo event generation. Tutorial We have prepared a noteb
Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer"
StyleAttack Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer" Prepare Pois