537 Repositories
Python unrestricted-adversarial-examples Libraries
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
Examples and code for the Practical Machine Learning workshop series
Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic
Adversarial Color Enhancement: Generating Unrestricted Adversarial Images by Optimizing a Color Filter
ACE Please find the preliminary version published at BMVC 2020 in the folder BMVC_version, and its extended journal version in Journal_version. Datase
Code for the paper: Adversarial Training Against Location-Optimized Adversarial Patches. ECCV-W 2020.
Adversarial Training Against Location-Optimized Adversarial Patches arXiv | Paper | Code | Video | Slides Code for the paper: Sukrut Rao, David Stutz,
Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two
512x512 flowers after 12 hours of training, 1 gpu 256x256 flowers after 12 hours of training, 1 gpu Pizza 'Lightweight' GAN Implementation of 'lightwe
Several simple examples for popular neural network toolkits calling custom CUDA operators.
Neural Network CUDA Example Several simple examples for neural network toolkits (PyTorch, TensorFlow, etc.) calling custom CUDA operators. We provide
Source code, datasets and trained models for the paper Learning Advanced Mathematical Computations from Examples (ICLR 2021), by François Charton, Amaury Hayat (ENPC-Rutgers) and Guillaume Lample
Maths from examples - Learning advanced mathematical computations from examples This is the source code and data sets relevant to the paper Learning a
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021) An efficient PyTorch library for Point Cloud Completion.
Page to PAGE Layout Analysis Tool
P2PaLA Page to PAGE Layout Analysis (P2PaLA) is a toolkit for Document Layout Analysis based on Neural Networks. 💥 Try our new DEMO for online baseli
[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks, ICLR 2021 (Spotlight) Demo | Paper [NEW!] Time to play with our interac
CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"
Diverse Structure Inpainting ArXiv | Papar | Supplementary Material | BibTex This repository is for the CVPR 2021 paper, "Generating Diverse Structure
Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)
Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train
Old Photo Restoration (Official PyTorch Implementation)
Bringing Old Photo Back to Life (CVPR 2020 oral)
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Anycost GAN video | paper | website Anycost GANs for Interactive Image Synthesis and Editing Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zh
Consistency Regularization for Adversarial Robustness
Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho
Speech Enhancement Generative Adversarial Network Based on Asymmetric AutoEncoder
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
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
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra
Code examples for my Write Better Python Code series on YouTube.
Write Better Python Code This repository contains the code examples used in my Write Better Python Code series published on YouTube: https:/
Streamlit dashboard examples - Twitter cashtags, StockTwits, WSB, Charts, SQL Pattern Scanner
streamlit-dashboards Streamlit dashboard examples - Twitter cashtags, StockTwits, WSB, Charts, SQL Pattern Scanner Tutorial Video https://ww
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Official implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis https://arxiv.org/abs/2011.13775
CIPS -- Official Pytorch Implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis Requirements pip install -r requi
Sandwich Batch Normalization
Sandwich Batch Normalization Code for Sandwich Batch Normalization. Introduction We present Sandwich Batch Normalization (SaBN), an extremely easy imp
Examples to accompany the
Examples to accompany the "Raspberry Pi Pico Python SDK" book published by Raspberry Pi Trading, which forms part of the technical documentation in support of Raspberry Pi Pico and the MicroPython port to RP2040.
Official implementation of the ICLR 2021 paper
You Only Need Adversarial Supervision for Semantic Image Synthesis Official PyTorch implementation of the ICLR 2021 paper "You Only Need Adversarial S
CharacterGAN: Few-Shot Keypoint Character Animation and Reposing
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
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
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model The task of age transformation illustrates the change of an individual
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN
artificial intelligence cosmic love and attention fire in the sky a pyramid made of ice a lonely house in the woods marriage in the mountains lantern
Unadversarial Examples: Designing Objects for Robust Vision
Unadversarial Examples: Designing Objects for Robust Vision This repository contains the code necessary to replicate the major results of our paper: U
This repository contains code examples and documentation for learning how applications can be developed with Kubernetes
BigBitBus KAT Components Click on the diagram to enlarge, or follow this link for detailed documentation Introduction Welcome to the BigBitBus Kuberne
Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information. :godmode:
ViZDoom ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research
🗣️ NALP is a library that covers Natural Adversarial Language Processing.
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!
Image-to-Image Translation with Conditional Adversarial Networks (Pix2pix) implementation in keras
pix2pix-keras Pix2pix implementation in keras. Original paper: Image-to-Image Translation with Conditional Adversarial Networks (pix2pix) Paper Author
Launched in 2018 Actively developed and supported. Supports tkinter, Qt, WxPython, Remi (in browser). Create custom layout GUI's simply. Python 2.7 & 3 Support. 200+ Demo programs & Cookbook for rapid start. Extensive documentation. Examples using Machine Learning(GUI, OpenCV Integration, Chatterbot), Floating Desktop Widgets, Matplotlib + Pyplot integration, add GUI to command line scripts, PDF & Image Viewer. For both beginning and advanced programmers .
Python GUIs for Humans Transforms the tkinter, Qt, WxPython, and Remi (browser-based) GUI frameworks into a simpler interface. The window definition i
Minimal examples of data structures and algorithms in Python
Pythonic Data Structures and Algorithms Minimal and clean example implementations of data structures and algorithms in Python 3. Contributing Thanks f