Python Adversarial Resources

Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho

ASEGAN: Speech Enhancement Generative Adversarial Network Based on Asymmetric AutoEncoder 中文版简介 Readme with English Version 介绍 基于SEGAN模型的改进版本，使用自主设计的非

GANsformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick *I wish to thank Christopher D. Manning for the fruitf

Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

CIPS -- Official Pytorch Implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis Requirements pip install -r requi

Sandwich Batch Normalization Code for Sandwich Batch Normalization. Introduction We present Sandwich Batch Normalization (SaBN), an extremely easy imp

You Only Need Adversarial Supervision for Semantic Image Synthesis Official PyTorch implementation of the ICLR 2021 paper "You Only Need Adversarial S

CharacterGAN Implementation of the paper "CharacterGAN: Few-Shot Keypoint Character Animation and Reposing" by Tobias Hinz, Matthew Fisher, Oliver Wan

InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective This is the official code base for our ICLR 2021 paper

Only a Matter of Style: Age Transformation Using a Style-Based Regression Model The task of age transformation illustrates the change of an individual

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NALP: Natural Adversarial Language Processing Welcome to NALP. Have you ever wanted to create natural text from raw sources? If yes, NALP is for you!

pix2pix-keras Pix2pix implementation in keras. Original paper: Image-to-Image Translation with Conditional Adversarial Networks (pix2pix) Paper Author