Python Adversarial-autoencoders Resources

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is

On Adversarial Robustness: A Neural Architecture Search perspective Preparation: Clone the repository: https://github.com/tdchaitanya/nas-robustness.g

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p

Adversarial Autoencoders (with Pytorch) Dependencies argparse time torch torchvision numpy itertools matplotlib Create Datasets python create_datasets

Cross Domain Facial Expression Recognition Benchmark Implementation of papers: Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchm

HiT-GAN Official TensorFlow Implementation HiT-GAN presents a Transformer-based generator that is trained based on Generative Adversarial Networks (GA

Code for the paper: Adversarial Machine Learning: Bayesian Perspectives This repository contains code for reproducing the experiments in the ** Advers

680 Final Project: BicycleGAN Haoran Tang Instructions 1. Training To train the network, please run train.py. Change hyper-parameters and folder paths

StyleSwin This repo is the official implementation of "StyleSwin: Transformer-based GAN for High-resolution Image Generation". By Bowen Zhang, Shuyang

An AI for Music Generation

Super Resolution Examples We run this script under TensorFlow 2.0 and the TensorLayer2.0+. For TensorLayer 1.4 version, please check release. 🚀 🚀 🚀

Leaded Gradient Method (LGM) This repository contains the PyTorch implementation for paper Dynamics-aware Adversarial Attack of 3D Sparse Convolution

CMUA-Watermark The official code for CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes (AAAI2022) arxiv. It is bas

HyperGBM Doc | 中文 We Are Hiring！ Dear folks,we are offering challenging opportunities located in Beijing for both professionals and students who are k

Contents Local and Global GAN Cross-View Image Translation Semantic Image Synthesis Acknowledgments Related Projects Citation Contributions Collaborat

SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your

AdversarialTexture Adversarial Texture Optimization from RGB-D Scans (CVPR 2020). Scanning Data Download Please refer to data directory for details. B

Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations This is the authors' implementation of Unsupervised Adversarial Learning of

Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks Stable Neural ODE with Lyapunov-Stable Equilibrium

Adversarial Learning for Modeling Human Motion This repository contains the open source code which reproduces the results for the paper: Adversarial l

Merel-MoCap-GAIL An implementation of Merel et al.'s paper on generative adversarial imitation learning (GAIL) using motion capture (MoCap) data: Lear

Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Trevor Ablett*, Bryan Chan*,

Vision-aided GAN video (3m) | website | paper Can the collective knowledge from a large bank of pretrained vision models be leveraged to improve GAN t

TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting Project Page | YouTube | Paper This is the official PyTorch implementation of the C

Data-Efficient GANs with DiffAugment project | paper | datasets | video | slides Generated using only 100 images of Obama, grumpy cats, pandas, the Br

GANformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick Update: We released the new GANformer2 paper! *I wish to thank Ch

Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code

Adversarial Examples for Extreme Multilabel Text Classification The code is adapted from the source codes of BERT-ATTACK [1], APLC_XLNet [2], and Atte

ESRGAN generate high quality pictures. GAN. Generative Adversarial Networks """ Super-resolution of CelebA using Generative Adversarial Networks. The

Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks This is the code for reproducing the results of th

A framework for adversarial attacks against token classification models

Cycle Consistent Adversarial Domain Adaptation (CyCADA) A pytorch implementation of CyCADA. If you use this code in your research please consider citi

An Open Source Project from the Data to AI Lab, at MIT Website: https://sdv.dev Documentation: https://sdv.dev/SDV User Guides Developer Guides Github

A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis Project Page | Paper A Shading-Guided Generative Implicit Model

mae-repo PyTorch re-implememtation of "masked autoencoders are scalable vision learners". In this repo, it heavily borrows codes from codebase https:/

A Shared Representation for Photorealistic Driving Simulators The official code for the paper: "A Shared Representation for Photorealistic Driving Sim

Visual Adversarial Imitation Learning using Variational Models (VMAIL) This is the official implementation of the NeurIPS 2021 paper. Project website

Patch-wise Adversarial Removal Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal

S-attack library: A library for evaluating trajectory prediction models This library contains two research projects to assess the trajectory predictio

Adversarial Differentiable Data Augmentation This repository provides the official PyTorch implementation of the ICRA 2021 paper: Adversarial Differen

DCGAN in TensorLayer This is the TensorLayer implementation of Deep Convolutional Generative Adversarial Networks. Looking for Text to Image Synthesis

Text To Image Synthesis This is a tensorflow implementation of synthesizing images. The images are synthesized using the GAN-CLS Algorithm from the pa

Unsupervised Image to Image Translation with Generative Adversarial Networks Paper: Unsupervised Image to Image Translation with Generative Adversaria

DAGAN This is the official implementation code for DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruct

Adversrial Machine Learning Benchmarks This code belongs to the papers: Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness? Det

Pytorch implementation of VQVAE. This paper combines 2 tricks: Vector Quantization (check out this amazing blog for better understanding.) Straight-Th

Adversarial Purification with Score-based Generative Models by Jongmin Yoon, Sung Ju Hwang, Juho Lee This repository includes the official PyTorch imp

Adversarial score matching and improved sampling for image generation This repo contains the official implementation for the ICLR 2021 paper Adversari

VILLA: Vision-and-Language Adversarial Training This is the official repository of VILLA (NeurIPS 2020 Spotlight). This repository currently supports

Autoencoders pretraining using clustering

Introduction This repository contains the code for the paper Sentence Bottleneck Autoencoders from Transformer Language Models by Ivan Montero, Nikola

BERT-ATTACK Code for our EMNLP2020 long paper: BERT-ATTACK: Adversarial Attack Against BERT Using BERT Dependencies Python 3.7 PyTorch 1.4.0 transform

TextFooler A Model for Natural Language Attack on Text Classification and Inference This is the source code for the paper: Jin, Di, et al. "Is BERT Re

CDAN Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018) New version: https://github.com/thuml/Transfer-Learning-Library Dataset

Generative Image Inpainting An open source framework for generative image inpainting task, with the support of Contextual Attention (CVPR 2018) and Ga

HAABSAStar Code for "Adversarial Training for a Hybrid Approach to Aspect-Based Sentiment Analysis". This project builds on the code from https://gith

Neighborhood Reconstructing Autoencoders The official repository for Neighborhood Reconstructing Autoencoders (Lee, Kwon, and Park, NeurIPS 2021). T

Adversarial Attacks on Graph Classification via Bayesian Optimisation @ NeurIPS 2021 This repository contains the official implementation of GRABNEL,

Learning Transferable Adversarial Perturbations This is an official release of the paper Learning Transferable Adversarial Perturbations. The code is

Adversarial Reweighting for Partial Domain Adaptation Code for paper "Xiang Gu, Xi Yu, Yan Yang, Jian Sun, Zongben Xu, Adversarial Reweighting for Par

Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples This repository is the official implementation of "Tow

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators [Project Website] [Replicate.ai Project] StyleGAN-NADA: CLIP-Guided Domain Adaptation

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation We present a generic image-to-image translation framework, pixel2style2pixel (pSp

This repository is the official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness. Requirements pip install -r requi

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository provides the official PyTorch implementation

OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi

Fast mesh denoising with data driven normal filtering using deep variational autoencoders This is an implementation for the paper entitled "Fast mesh

Subspace Adversarial Training Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust. However,

A framework that constructs deep neural networks, autoencoders, logistic regressors, and linear networks without the use of any outside machine learning libraries - all from scratch.

OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi

FAME: Feature-based Adversarial Meta-Embeddings This is the companion code for the experiments reported in the paper "FAME: Feature-Based Adversarial

Adversarial Neuron Pruning Purifies Backdoored Deep Models Code for NeurIPS 2021 "Adversarial Neuron Pruning Purifies Backdoored Deep Models" by Dongx

Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without

CelebAMask-HQ [Paper] [Demo] CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA da

Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning (c) Tianyu Han and Daniel Truhn, RWTH Aachen University, 20

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network Pytorch implementation for our DivCo. We propose a simple ye

ImageNet Adversarial Image Evaluation This repository contains the code and some materials used in the experimental work presented in the following pa

MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been

GANSpace: Discovering Interpretable GAN Controls Figure 1: Sequences of image edits performed using control discovered with our method, applied to thr

GROOT: Growing Robust Trees Growing Robust Trees (GROOT) is an algorithm that fits binary classification decision trees such that they are robust agai

A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.

Resilience from Diversity: Population-based approach to harden models against adversarial attacks Requirements To install requirements: pip install -r

RecGURU About The Project Source code and baselines for the RecGURU paper "RecGURU: Adversarial Learning of Generalized User Representations for Cross

Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li

faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness (NeurIPS2021) This repository contains code for the paper "Smo

An pytorch implementation of Masked Autoencoders Are Scalable Vision Learners This is a coarse version for MAE, only make the pretrain model, the fine

BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation Official PyTorch implementation of the NeurIPS 2021 paper Mingcong Liu, Qiang

MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup

alpha-GAN Unofficial pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks." arXi

Experimental code for paper: Generative Adversarial Networks as Variational Training of Energy Based Models, under review at ICLR 2017 requirements: T

Generating Videos with Scene Dynamics This repository contains an implementation of Generating Videos with Scene Dynamics by Carl Vondrick, Hamed Pirs

Unrolled Generative Adversarial Networks Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein arxiv:1611.02163 This repo contains an example notebo

Chainer-GAN-lib This repository collects chainer implementation of state-of-the-art GAN algorithms. These codes are evaluated with the inception score

Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the

SeqGAN Requirements: Tensorflow r1.0.1 Python 2.7 CUDA 7.5+ (For GPU) Introduction Apply Generative Adversarial Nets to generating sequences of discre