6866 Repositories
Python pytorch-federated-learning Libraries
Official repository for MixFaceNets: Extremely Efficient Face Recognition Networks
MixFaceNets This is the official repository of the paper: MixFaceNets: Extremely Efficient Face Recognition Networks. (Accepted in IJCB2021) https://i
Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators..
ARAPReg Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators.. Installation The cod
Empower Sequence Labeling with Task-Aware Language Model
LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra
PyTorch DepthNet Training on Still Box dataset
DepthNet training on Still Box Project page This code can replicate the results of our paper that was published in UAVg-17. If you use this repo in yo
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade
E2C implementation in PyTorch
Embed to Control implementation in PyTorch Paper can be found here: https://arxiv.org/abs/1506.07365 You will need a patched version of OpenAI Gym in
3D ResNets for Action Recognition (CVPR 2018)
3D ResNets for Action Recognition Update (2020/4/13) We published a paper on arXiv. Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara, and Yutaka Satoh,
"Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback"
This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.
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-a2c-ppo-acktr Update (April 12th, 2021) PPO is great, but Soft Actor Critic can be better for many continuous control tasks. Please check out
PyTorch experiments with the Zalando fashion-mnist dataset
zalando-pytorch PyTorch experiments with the Zalando fashion-mnist dataset Project Organization ├── LICENSE ├── Makefile - Makefile with co
A PyTorch Implementation of SphereFace.
SphereFace A PyTorch Implementation of SphereFace. The code can be trained on CASIA-Webface and the best accuracy on LFW is 99.22%. SphereFace: Deep H
A working implementation of the Categorical DQN (Distributional RL).
Categorical DQN. Implementation of the Categorical DQN as described in A distributional Perspective on Reinforcement Learning. Thanks to @tudor-berari
Neural Turing Machines (NTM) - PyTorch Implementation
PyTorch Neural Turing Machine (NTM) PyTorch implementation of Neural Turing Machines (NTM). An NTM is a memory augumented neural network (attached to
Code for the SIGGRAPH 2021 paper "Consistent Depth of Moving Objects in Video".
Consistent Depth of Moving Objects in Video This repository contains training code for the SIGGRAPH 2021 paper "Consistent Depth of Moving Objects in
An official implementation of "Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation" (ICCV 2021) in PyTorch.
Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation This is an official implementation of the paper "Exploiting a Joint
A curated list of resources for Image and Video Deblurring
A curated list of resources for Image and Video Deblurring
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models. Everything is pure Python and PyTorch based to keep it as simple and beginner-friendly, yet powerful as possible.
yolox_backbone is a deep-learning library and is a collection of YOLOX Backbone models.
YOLOX-Backbone yolox-backbone is a deep-learning library and is a collection of YOLOX backbone models. Install pip install yolox-backbone Load a Pret
Transformer model implemented with Pytorch
transformer-pytorch Transformer model implemented with Pytorch Attention is all you need-[Paper] Architecture Self-Attention self_attention.py class
Korean Simple Contrastive Learning of Sentence Embeddings using SKT KoBERT and kakaobrain KorNLU dataset
KoSimCSE Korean Simple Contrastive Learning of Sentence Embeddings implementation using pytorch SimCSE Installation git clone https://github.com/BM-K/
Learning source code review, spot vulnerability, find some ways how to fix it.
Learn Source Code Review Learning source code review, spot vulnerability, find some ways how to fix it. WordPress Plugin Authenticated Stored XSS on C
Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision (ICCV 2021)
Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision (ICCV 2021) PyTorch implementation of Learning RAW-to-sRGB Mappings with Inaccurat
The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"
SIGIR2021-EGLN The implement of paper "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization" Neural graph based Col
Easy to use Audio Tagging in PyTorch
Audio Classification, Tagging & Sound Event Detection in PyTorch Progress: Fine-tune on audio classification Fine-tune on audio tagging Fine-tune on s
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
Guesslang detects the programming language of a given source code
Detect the programming language of a source code
pix2tex: Using a ViT to convert images of equations into LaTeX code.
The goal of this project is to create a learning based system that takes an image of a math formula and returns corresponding LaTeX code.
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv
PyTorch implementation of MoCo v3 for self-supervised ResNet and ViT.
MoCo v3 for Self-supervised ResNet and ViT Introduction This is a PyTorch implementation of MoCo v3 for self-supervised ResNet and ViT. The original M
Learning Compatible Embeddings, ICCV 2021
LCE Learning Compatible Embeddings, ICCV 2021 by Qiang Meng, Chixiang Zhang, Xiaoqiang Xu and Feng Zhou Paper: Arxiv We cannot release source codes pu
[ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization Kaidi Cao, Yining Chen, Junwei Lu, Nikos Arechiga, Adrien Gaidon, Tengyu Ma
This repository is the offical Pytorch implementation of ContextPose: Context Modeling in 3D Human Pose Estimation: A Unified Perspective (CVPR 2021).
Context Modeling in 3D Human Pose Estimation: A Unified Perspective (CVPR 2021) Introduction This repository is the offical Pytorch implementation of
Parametric Contrastive Learning (ICCV2021)
Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or
Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"
CoTuning Official implementation for NeurIPS 2020 paper Co-Tuning for Transfer Learning. [News] 2021/01/13 The COCO 70 dataset used in the paper is av
Towards Interpretable Deep Metric Learning with Structural Matching
DIML Created by Wenliang Zhao*, Yongming Rao*, Ziyi Wang, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for paper Towards Interpr
Pytorch Implementation for NeurIPS (oral) paper: Pixel Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation
Pixel-Level Cycle Association This is the Pytorch implementation of our NeurIPS 2020 Oral paper Pixel-Level Cycle Association: A New Perspective for D
Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision. ICCV 2021.
Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision Download links and PyTorch implementation of "Towers of Ba
Official PyTorch implementation of the paper: Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Official PyTorch implementation of the paper: Improving Graph Neural Net
Reference code for the paper CAMS: Color-Aware Multi-Style Transfer.
CAMS: Color-Aware Multi-Style Transfer Mahmoud Afifi1, Abdullah Abuolaim*1, Mostafa Hussien*2, Marcus A. Brubaker1, Michael S. Brown1 1York University
A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild"
VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild A pytorch implementation of the CVPR2021 paper "VSPW: A Large-scale Dataset for Video
Convert Apple NeuralHash model for CSAM Detection to ONNX.
Apple NeuralHash is a perceptual hashing method for images based on neural networks. It can tolerate image resize and compression.
PyTorch implementation of "Learn to Dance with AIST++: Music Conditioned 3D Dance Generation."
Learn to Dance with AIST++: Music Conditioned 3D Dance Generation. Installation pip install -r requirements.txt Prepare Dataset bash data/scripts/pre
In this project we investigate the performance of the SetCon model on realistic video footage. Therefore, we implemented the model in PyTorch and tested the model on two example videos.
Contrastive Learning of Object Representations Supervisor: Prof. Dr. Gemma Roig Institutions: Goethe University CVAI - Computational Vision & Artifici
Official PyTorch implementation of the paper "Recycling Discriminator: Towards Opinion-Unaware Image Quality Assessment Using Wasserstein GAN", accepted to ACM MM 2021 BNI Track.
RecycleD Official PyTorch implementation of the paper "Recycling Discriminator: Towards Opinion-Unaware Image Quality Assessment Using Wasserstein GAN
Customizable RecSys Simulator for OpenAI Gym
gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
MINERVA: An out-of-the-box GUI tool for offline deep reinforcement learning
MINERVA is an out-of-the-box GUI tool for offline deep reinforcement learning, designed for everyone including non-programmers to do reinforcement learning as a tool.
YOLOX + ROS(1, 2) object detection package
YOLOX + ROS(1, 2) object detection package
PyTorch implementations for our SIGGRAPH 2021 paper: Editable Free-viewpoint Video Using a Layered Neural Representation.
st-nerf We provide PyTorch implementations for our paper: Editable Free-viewpoint Video Using a Layered Neural Representation SIGGRAPH 2021 Jiakai Zha
Official implementation of Meta-StyleSpeech and StyleSpeech
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code
LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data arXiv This is the code base for weakly supervised NER. We provide a
A "gym" style toolkit for building lightweight Neural Architecture Search systems
A "gym" style toolkit for building lightweight Neural Architecture Search systems
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
Ἀνατομή is a PyTorch library to analyze representation of neural networks
Ἀνατομή is a PyTorch library to analyze representation of neural networks
Keras like implementation of Deep Learning architectures from scratch using numpy.
Mini-Keras Keras like implementation of Deep Learning architectures from scratch using numpy. How to contribute? The project contains implementations
Open source implementation of AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing
AceNAS This repo is the experiment code of AceNAS, and is not considered as an official release. We are working on integrating AceNAS as a built-in st
This is the official code of our paper "Diversity-based Trajectory and Goal Selection with Hindsight Experience Relay" (PRICAI 2021)
Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay This is the official implementation of our paper "Diversity-based Traje
Learn meanings behind words is a key element in NLP. This project concentrates on the disambiguation of preposition senses. Therefore, we train a bert-transformer model and surpass the state-of-the-art.
New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa
PyTorch implementation of spectral graph ConvNets, NIPS’16
Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson
A pytorch implementation of faster RCNN detection framework (Use detectron2, it's a masterpiece)
Notice(2019.11.2) This repo was built back two years ago when there were no pytorch detection implementation that can achieve reasonable performance.
😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc
------ Update September 2018 ------ It's been a year since TorchMoji and DeepMoji were released. We're trying to understand how it's being used such t
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da
PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM
Quasi-Recurrent Neural Network (QRNN) for PyTorch Updated to support multi-GPU environments via DataParallel - see the the multigpu_dataparallel.py ex
Skipgram Negative Sampling in PyTorch
PyTorch SGNS Word2Vec's SkipGramNegativeSampling in Python. Yet another but quite general negative sampling loss implemented in PyTorch. It can be use
Pytorch version of SfmLearner from Tinghui Zhou et al.
SfMLearner Pytorch version This codebase implements the system described in the paper: Unsupervised Learning of Depth and Ego-Motion from Video Tinghu
PyTorch implementation of Deformable Convolution
Deformable Convolutional Networks in PyTorch This repo is an implementation of Deformable Convolution. Ported from author's MXNet implementation. Buil
Pytorch implementation for reproducing StackGAN_v2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
StackGAN-v2 StackGAN-v1: Tensorflow implementation StackGAN-v1: Pytorch implementation Inception score evaluation Pytorch implementation for reproduci
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin
Graph Convolutional Networks in PyTorch
Graph Convolutional Networks in PyTorch PyTorch implementation of Graph Convolutional Networks (GCNs) for semi-supervised classification [1]. For a hi
IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020)
This repo is the official implementation of our paper "Instance Adaptive Self-training for Unsupervised Domain Adaptation". The purpose of this repo is to better communicate with you and respond to your questions. This repo is almost the same with Another-Version, and you can also refer to that version.
Refactoring dalle-pytorch and taming-transformers for TPU VM
Text-to-Image Translation (DALL-E) for TPU in Pytorch Refactoring Taming Transformers and DALLE-pytorch for TPU VM with Pytorch Lightning Requirements
Learning and Building Convolutional Neural Networks using PyTorch
Image Classification Using Deep Learning Learning and Building Convolutional Neural Networks using PyTorch. Models, selected are based on number of ci
[TOG 2021] PyTorch implementation for the paper: SofGAN: A Portrait Image Generator with Dynamic Styling.
This repository contains the official PyTorch implementation for the paper: SofGAN: A Portrait Image Generator with Dynamic Styling. We propose a SofGAN image generator to decouple the latent space of portraits into two subspaces: a geometry space and a texture space. Experiments on SofGAN show that our system can generate high quality portrait images with independently controllable geometry and texture attributes.
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020
TDANet: Text-Guided Neural Image Inpainting, MM'2020 (Oral) MM | ArXiv This repository implements the paper "Text-Guided Neural Image Inpainting" by L
Extreme Rotation Estimation using Dense Correlation Volumes
Extreme Rotation Estimation using Dense Correlation Volumes This repository contains a PyTorch implementation of the paper: Extreme Rotation Estimatio
robomimic: A Modular Framework for Robot Learning from Demonstration
robomimic [Homepage]   [Documentation]   [Study Paper]   [Study Website]   [ARISE Initiative] Latest Updates [08/09/2021] v0.1.0: Initial code and pap
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
Contrastive Learning for Compact Single Image Dehazing, CVPR2021
AECR-Net Contrastive Learning for Compact Single Image Dehazing, CVPR2021. Official Pytorch based implementation. Paper arxiv Pytorch Version TODO: mo
PyTorch implementation for paper Neural Marching Cubes.
NMC PyTorch implementation for paper Neural Marching Cubes, Zhiqin Chen, Hao Zhang. Paper | Supplementary Material (to be updated) Citation If you fin
FedScale: Benchmarking Model and System Performance of Federated Learning
FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca
Code accompanying our paper Feature Learning in Infinite-Width Neural Networks
Empirical Experiments in "Feature Learning in Infinite-width Neural Networks" This repo contains code to replicate our experiments (Word2Vec, MAML) in
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l
PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis
Daft-Exprt - PyTorch Implementation PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis The
PyTorch implementation of Neural Dual Contouring.
NDC PyTorch implementation of Neural Dual Contouring. Citation We are still writing the paper while adding more improvements and applications. If you
PyTorch implementation of ShapeConv: Shape-aware Convolutional Layer for RGB-D Indoor Semantic Segmentation.
Shape-aware Convolutional Layer (ShapeConv) PyTorch implementation of ShapeConv: Shape-aware Convolutional Layer for RGB-D Indoor Semantic Segmentatio
Neural network visualization toolkit for tf.keras
Neural network visualization toolkit for tf.keras
Natural Language Processing library built with AllenNLP 🌲🌱
Custom Natural Language Processing with big and small models 🌲🌱
Official implementation for ICDAR 2021 paper "Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer"
Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer Description Convert offline handwritten mathematical expressi
This repository contains PyTorch models for SpecTr (Spectral Transformer).
SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation This repository contains PyTorch models for SpecTr (Spectral Transformer).
PyTorch implementation for Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition.
Stochastic CSLR This is the PyTorch implementation for the ECCV 2020 paper: Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuou
Sign Language Translation with Transformers (COLING'2020, ECCV'20 SLRTP Workshop)
transformer-slt This repository gathers data and code supporting the experiments in the paper Better Sign Language Translation with STMC-Transformer.
Official PyTorch implementation of Segmenter: Transformer for Semantic Segmentation
Segmenter: Transformer for Semantic Segmentation Segmenter: Transformer for Semantic Segmentation by Robin Strudel*, Ricardo Garcia*, Ivan Laptev and
This is an official implementation for "Self-Supervised Learning with Swin Transformers".
Self-Supervised Learning with Vision Transformers By Zhenda Xie*, Yutong Lin*, Zhuliang Yao, Zheng Zhang, Qi Dai, Yue Cao and Han Hu This repo is the
Using VideoBERT to tackle video prediction
VideoBERT This repo reproduces the results of VideoBERT (https://arxiv.org/pdf/1904.01766.pdf). Inspiration was taken from https://github.com/MDSKUL/M
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery
A powerful and flexible machine learning platform for drug discovery
StarGAN-ZSVC: Unofficial PyTorch Implementation
This repository is an unofficial PyTorch implementation of StarGAN-ZSVC by Matthew Baas and Herman Kamper. This repository provides both model architectures and the code to inference or train them.
DockStream: A Docking Wrapper to Enhance De Novo Molecular Design
DockStream Description DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution an
AutoVideo: An Automated Video Action Recognition System
AutoVideo is a system for automated video analysis. It is developed based on D3M infrastructure, which describes machine learning with generic pipeline languages. Currently, it focuses on video action recognition, supporting various state-of-the-art video action recognition algorithms. It also supports automated model selection and hyperparameter tuning. AutoVideo is developed by DATA Lab at Texas A&M University.