1128 Repositories
Python virtual-adversarial-training Libraries
Code for "ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on", accepted at WACV 2021 Generation of Human Behavior Workshop.
ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on [ Paper ] [ Project Page ] This repository contains the code fo
Contextualized Perturbation for Textual Adversarial Attack, NAACL 2021
Contextualized Perturbation for Textual Adversarial Attack Introduction This is a PyTorch implementation of Contextualized Perturbation for Textual Ad
Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models
Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN.
Ryan Murdock has done it again, combining OpenAI's CLIP and the generator from a BigGAN! This repository wraps up his work so it is easily accessible to anyone who owns a GPU.
Official repository for Jia, Raghunathan, Göksel, and Liang, "Certified Robustness to Adversarial Word Substitutions" (EMNLP 2019)
Certified Robustness to Adversarial Word Substitutions This is the official GitHub repository for the following paper: Certified Robustness to Adversa
HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks
HiFiGAN Denoiser This is a Unofficial Pytorch implementation of the paper HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep F
Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation.
Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation. It was introduced in Wright, Logan G. & Onodera, Tatsuhiro et al. (2021)1 to train Physical Neural Networks (PNNs) - neural networks whose building blocks are physical systems.
Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow.
Denoised-Smoothing-TF Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow. Denoised Smoothing is
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
Self-Supervised Vision Transformers with DINO PyTorch implementation and pretrained models for DINO. For details, see Emerging Properties in Self-Supe
Invert and perturb GAN images for test-time ensembling
GAN Ensembling Project Page | Paper | Bibtex Ensembling with Deep Generative Views. Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhan
Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"
This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea
[CVPR 2021] MiVOS - Mask Propagation module. Reproduced STM (and better) with training code :star2:. Semi-supervised video object segmentation evaluation.
MiVOS (CVPR 2021) - Mask Propagation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] [Papers with Code] This repo impleme
TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards
TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers (e.g., ViT, BERT and GPT) or huge classes (millions). It has the same API design as PyTorch.
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
collie_recs Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Coll
Code for Dual Contrastive Learning for Unsupervised Image-to-Image Translation, NTIRE, CVPRW 2021.
arXiv Dual Contrastive Learning Adversarial Generative Networks (DCLGAN) We provide our PyTorch implementation of DCLGAN, which is a simple yet powerf
A Practical Debugging Tool for Training Deep Neural Networks
Cockpit is a visual and statistical debugger specifically designed for deep learning!
PlenOctrees: NeRF-SH Training & Conversion
PlenOctrees Official Repo: NeRF-SH training and conversion This repository contains code to train NeRF-SH and to extract the PlenOctree, constituting
Pytorch implementation of "Training a 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet"
Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te
FID calculation with proper image resizing and quantization steps
clean-fid: Fixing Inconsistencies in FID Project | Paper The FID calculation involves many steps that can produce inconsistencies in the final metric.
(CVPR 2021) ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection
ST3D Code release for the paper ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection, CVPR 2021 Authors: Jihan Yang*, Shaoshu
Coreference resolution for English, German and Polish, optimised for limited training data and easily extensible for further languages
Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1
Training code of Spatial Time Memory Network. Semi-supervised video object segmentation.
Training-code-of-STM This repository fully reproduces Space-Time Memory Networks Performance on Davis17 val set&Weights backbone training stage traini
transfer attack; adversarial examples; black-box attack; unrestricted Adversarial Attacks on ImageNet; CVPR2021 天池黑盒竞赛
transfer_adv CVPR-2021 AIC-VI: unrestricted Adversarial Attacks on ImageNet CVPR2021 安全AI挑战者计划第六期赛道2:ImageNet无限制对抗攻击 介绍 : 深度神经网络已经在各种视觉识别问题上取得了最先进的性能。
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet, CVPR2021 安全AI挑战者计划第六期:ImageNet无限制对抗攻击 决赛第四名(team name: Advers)
Focus on Algorithm Design, Not on Data Wrangling
The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.
Disentangled Cycle Consistency for Highly-realistic Virtual Try-On, CVPR 2021
Disentangled Cycle Consistency for Highly-realistic Virtual Try-On, CVPR 2021 [WIP] The code for CVPR 2021 paper 'Disentangled Cycle Consistency for H
skweak: A software toolkit for weak supervision applied to NLP tasks
Labelled data remains a scarce resource in many practical NLP scenarios. This is especially the case when working with resource-poor languages (or text domains), or when using task-specific labels without pre-existing datasets. The only available option is often to collect and annotate texts by hand, which is expensive and time-consuming.
Source code for AAAI20 "Generating Persona Consistent Dialogues by Exploiting Natural Language Inference".
Generating Persona Consistent Dialogues by Exploiting Natural Language Inference Source code for RCDG model in AAAI20 Generating Persona Consistent Di
[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang
BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat
This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
BMW-Anonymization-Api Data privacy and individuals’ anonymity are and always have been a major concern for data-driven companies. Therefore, we design
Diffgram - Supervised Learning Data Platform
Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning
Official code of our work, Unified Pre-training for Program Understanding and Generation [NAACL 2021].
PLBART Code pre-release of our work, Unified Pre-training for Program Understanding and Generation accepted at NAACL 2021. Note. A detailed documentat
OpenMMLab Image and Video Editing Toolbox
Introduction MMEditing is an open source image and video editing toolbox based on PyTorch. It is a part of the OpenMMLab project. The master branch wo
Sandbox for training deep learning networks
Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (
Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face Manipulation" published in CVPR 2020.
FFD Source Code Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face M
Based on the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
Geometry-aware Instance-reweighted Adversarial Training This repository provides codes for Geometry-aware Instance-reweighted Adversarial Training (ht
Trading environnement for RL agents, backtesting and training.
TradzQAI Trading environnement for RL agents, backtesting and training. Live session with coinbasepro-python is finaly arrived ! Available sessions: L
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
TradingGym TradingGym is a toolkit for training and backtesting the reinforcement learning algorithms. This was inspired by OpenAI Gym and imitated th
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.
InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea
Code for pre-training CharacterBERT models (as well as BERT models).
Pre-training CharacterBERT (and BERT) This is a repository for pre-training BERT and CharacterBERT. DISCLAIMER: The code was largely adapted from an o
Official Implementation for "ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement" https://arxiv.org/abs/2104.02699
ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement Recently, the power of unconditional image synthesis has significantly advanced th
Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper
TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I
Adversarial Adaptation with Distillation for BERT Unsupervised Domain Adaptation
Knowledge Distillation for BERT Unsupervised Domain Adaptation Official PyTorch implementation | Paper Abstract A pre-trained language model, BERT, ha
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r
This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.
This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
SimplePose Code and pre-trained models for our paper, “Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation”, a
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,
[ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accep
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
High-level batteries-included neural network training library for Pytorch
Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st
higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.
higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these
Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)
News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which
Rembg Video Virtual Green Screen Edition
Rembg Virtual Greenscreen Edition is a tool to create a green screen matte for videos
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Introduction This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code her
Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters
Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage
A high performance and generic framework for distributed DNN training
BytePS BytePS is a high performance and general distributed training framework. It supports TensorFlow, Keras, PyTorch, and MXNet, and can run on eith
PyTorch extensions for high performance and large scale training.
Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
TensorTrade: Trade Efficiently with Reinforcement Learning TensorTrade is still in Beta, meaning it should be used very cautiously if used in producti
PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
Contrast to Divide: self-supervised pre-training for learning with noisy labels This is an official implementation of "Contrast to Divide: self-superv
Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks
PWLQ Updates 2020/07/16 - We are working on getting permission from our institution to release our source code. We will release it once we are granted
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.
Generate text images for training deep learning ocr model
New version release:https://github.com/oh-my-ocr/text_renderer Text Renderer Generate text images for training deep learning OCR model (e.g. CRNN). Su
A synthetic data generator for text recognition
TextRecognitionDataGenerator A synthetic data generator for text recognition What is it for? Generating text image samples to train an OCR software. N
Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
English | 简体中文 Introduction PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and a
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
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
Dataset Cartography Code for the paper Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics at EMNLP 2020. This repository cont
[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
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code here will be included in upstream Pytorch eventually. The intention of Apex is to make up-to-date utilities available to users as quickly as possible.
Old Photo Restoration (Official PyTorch Implementation)
Bringing Old Photo Back to Life (CVPR 2020 oral)
Official code of our work, Unified Pre-training for Program Understanding and Generation [NAACL 2021].
PLBART Code pre-release of our work, Unified Pre-training for Program Understanding and Generation accepted at NAACL 2021. Note. A detailed documentat
Ganeti is a virtual machine cluster management tool built on top of existing virtualization technologies such as Xen or KVM and other open source software.
Ganeti 3.0 =========== For installation instructions, read the INSTALL and the doc/install.rst files. For a brief introduction, read the ganeti(7) m
[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
[CVPR2021 Oral] UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers This is the official PyTorch implementation and models for UP-DETR paper: @a
Official code for "Parser-Free Virtual Try-on via Distilling Appearance Flows", CVPR 2021
Parser-Free Virtual Try-on via Distilling Appearance Flows, CVPR 2021 Official code for CVPR 2021 paper 'Parser-Free Virtual Try-on via Distilling App
Consistency Regularization for Adversarial Robustness
Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain
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
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built
Simple tools for logging and visualizing, loading and training
TNT TNT is a library providing powerful dataloading, logging and visualization utilities for Python. It is closely integrated with PyTorch and is desi
Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch
COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a
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
网络协议2天集训
网络协议2天集训 抓包工具安装 Wireshark wireshark下载地址 Tcpdump CentOS yum install tcpdump -y Ubuntu apt-get install tcpdump -y k8s抓包测试环境 查看虚拟网卡veth pair 查看
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
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
Simple tutorials on Pytorch DDP training
pytorch-distributed-training Distribute Dataparallel (DDP) Training on Pytorch Features Easy to study DDP training You can directly copy this code for
Learning to Initialize Neural Networks for Stable and Efficient Training
GradInit This repository hosts the code for experiments in the paper, GradInit: Learning to Initialize Neural Networks for Stable and Efficient Traini