3218 Repositories
Python face-uncertainty-pytorch Libraries
Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The original code is written in keras.
CasRel-pytorch-reimplement Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The o
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai
TraND: Transferable Neighborhood Discovery for Unsupervised Cross-domain Gait Recognition.
TraND This is the code for the paper "Jinkai Zheng, Xinchen Liu, Chenggang Yan, Jiyong Zhang, Wu Liu, Xiaoping Zhang and Tao Mei: TraND: Transferable
implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks
YOLOR implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks To reproduce the results in the paper, please us
PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"
UMS for Multi-turn Response Selection Implements the model described in the following paper Do Response Selection Models Really Know What's Next? Utte
FastFace: Lightweight Face Detection Framework
Light Face Detection using PyTorch Lightning
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020
PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021)
mlp-mixer-pytorch PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021) Usage import torch from mlp_mixer
An unofficial PyTorch implementation of a federated learning algorithm, FedAvg.
Federated Averaging (FedAvg) in PyTorch An unofficial implementation of FederatedAveraging (or FedAvg) algorithm proposed in the paper Communication-E
Implementation of ResMLP, an all MLP solution to image classification, in Pytorch
ResMLP - Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-py
Simple implementation of OpenAI CLIP model in PyTorch.
It was in January of 2021 that OpenAI announced two new models: DALL-E and CLIP, both multi-modality models connecting texts and images in some way. In this article we are going to implement CLIP model from scratch in PyTorch. OpenAI has open-sourced some of the code relating to CLIP model but I found it intimidating and it was far from something short and simple. I also came across a good tutorial inspired by CLIP model on Keras code examples and I translated some parts of it into PyTorch to build this tutorial totally with our beloved PyTorch!
Face Detection & Age Gender & Expression & Recognition
Face Detection & Age Gender & Expression & Recognition
Deep learning toolbox based on PyTorch for hyperspectral data classification.
Deep learning toolbox based on PyTorch for hyperspectral data classification.
NeRF Meta-Learning with PyTorch
NeRF Meta Learning With PyTorch nerf-meta is a PyTorch re-implementation of NeRF experiments from the paper "Learned Initializations for Optimizing Co
pytorch implementation of dftd2 & dftd3
torch-dftd pytorch implementation of dftd2 [1] & dftd3 [2, 3] Install # Install from pypi pip install torch-dftd # Install from source (for developer
An unopinionated replacement for PyTorch's Dataset and ImageFolder, that handles Tar archives
Simple Tar Dataset An unopinionated replacement for PyTorch's Dataset and ImageFolder classes, for datasets stored as uncompressed Tar archives. Just
A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.
Reinforcement Learning (PyTorch) 🤖 + 🍰 = ❤️ This repo will contain PyTorch implementation of various fundamental RL algorithms. It's aimed at making
Implementation for Paper "Inverting Generative Adversarial Renderer for Face Reconstruction"
StyleGAR TODO: add arxiv link Implementation of Inverting Generative Adversarial Renderer for Face Reconstruction TODO: for test Currently, some model
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models. Developers can reproduce these SOTA methods and build their own methods.
PyTorch implementation of MLP-Mixer
PyTorch implementation of MLP-Mixer MLP-Mixer: an all-MLP architecture composed of alternate token-mixing and channel-mixing operations. The token-mix
Fast, differentiable sorting and ranking in PyTorch
Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms
A fast Text-to-Speech (TTS) model. Work well for English, Mandarin/Chinese, Japanese, Korean, Russian and Tibetan (so far). 快速语音合成模型,适用于英语、普通话/中文、日语、韩语、俄语和藏语(当前已测试)。
简体中文 | English 并行语音合成 [TOC] 新进展 2021/04/20 合并 wavegan 分支到 main 主分支,删除 wavegan 分支! 2021/04/13 创建 encoder 分支用于开发语音风格迁移模块! 2021/04/13 softdtw 分支 支持使用 Sof
Modular and extensible speech recognition library leveraging pytorch-lightning and hydra.
Lightning ASR Modular and extensible speech recognition library leveraging pytorch-lightning and hydra What is Lightning ASR • Installation • Get Star
Pytorch implementation for "Adversarial Robustness under Long-Tailed Distribution" (CVPR 2021 Oral)
Adversarial Long-Tail This repository contains the PyTorch implementation of the paper: Adversarial Robustness under Long-Tailed Distribution, CVPR 20
Vision Transformer for 3D medical image registration (Pytorch).
ViT-V-Net: Vision Transformer for Volumetric Medical Image Registration keywords: vision transformer, convolutional neural networks, image registratio
This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting.
GAN Memory for Lifelong learning This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting. Please consider citing our paper
:hot_pepper: R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)
R²SQL The PyTorch implementation of paper Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing. (AAAI 2021) Requirement
[NeurIPS 2020] Blind Video Temporal Consistency via Deep Video Prior
pytorch-deep-video-prior (DVP) Official PyTorch implementation for NeurIPS 2020 paper: Blind Video Temporal Consistency via Deep Video Prior TensorFlo
DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control
DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control One version of our system is implemented using the
The pytorch implementation of DG-Font: Deformable Generative Networks for Unsupervised Font Generation
DG-Font: Deformable Generative Networks for Unsupervised Font Generation The source code for 'DG-Font: Deformable Generative Networks for Unsupervised
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.
YOLOv5 in PyTorch ONNX CoreML TFLite
This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and evolution on anonymized client datasets. All code and models are under active development, and are subject to modification or deletion without notice.
Reformer, the efficient Transformer, in Pytorch
Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH
Espresso: A Fast End-to-End Neural Speech Recognition Toolkit
Espresso Espresso is an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning libra
Fast, general, and tested differentiable structured prediction in PyTorch
Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
The PyTorch-Kaldi Speech Recognition Toolkit PyTorch-Kaldi is an open-source repository for developing state-of-the-art DNN/HMM speech recognition sys
Integrating the Best of TF into PyTorch, for Machine Learning, Natural Language Processing, and Text Generation. This is part of the CASL project: http://casl-project.ai/
Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar
Pytorch-Named-Entity-Recognition-with-BERT
BERT NER Use google BERT to do CoNLL-2003 NER ! Train model using Python and Inference using C++ ALBERT-TF2.0 BERT-NER-TENSORFLOW-2.0 BERT-SQuAD Requi
Unofficial PyTorch implementation of Google AI's VoiceFilter system
VoiceFilter Note from Seung-won (2020.10.25) Hi everyone! It's Seung-won from MINDs Lab, Inc. It's been a long time since I've released this open-sour
Google AI 2018 BERT pytorch implementation
BERT-pytorch Pytorch implementation of Google AI's 2018 BERT, with simple annotation BERT 2018 BERT: Pre-training of Deep Bidirectional Transformers f
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t
End-to-End Speech Processing Toolkit
ESPnet: end-to-end speech processing toolkit system/pytorch ver. 1.0.1 1.1.0 1.2.0 1.3.1 1.4.0 1.5.1 1.6.0 1.7.1 1.8.1 ubuntu18/python3.8/pip ubuntu18
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au
Pytorch NLP library based on FastAI
Quick NLP Quick NLP is a deep learning nlp library inspired by the fast.ai library It follows the same api as fastai and extends it allowing for quick
Pytorch implementation of Tacotron
Tacotron-pytorch A pytorch implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model. Requirements Install python 3 Install pytorc
An implementation of WaveNet with fast generation
pytorch-wavenet This is an implementation of the WaveNet architecture, as described in the original paper. Features Automatic creation of a dataset (t
Sequence-to-Sequence Framework in PyTorch
nmtpytorch allows training of various end-to-end neural architectures including but not limited to neural machine translation, image captioning and au
A PyTorch Implementation of End-to-End Models for Speech-to-Text
speech Speech is an open-source package to build end-to-end models for automatic speech recognition. Sequence-to-sequence models with attention, Conne
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod
Data manipulation and transformation for audio signal processing, powered by PyTorch
torchaudio: an audio library for PyTorch The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the
Interpretable Models for NLP using PyTorch
This repo is deprecated. Please find the updated package here. https://github.com/EdGENetworks/anuvada Anuvada: Interpretable Models for NLP using PyT
An open source framework for seq2seq models in PyTorch.
pytorch-seq2seq Documentation This is a framework for sequence-to-sequence (seq2seq) models implemented in PyTorch. The framework has modularized and
PyTorch ,ONNX and TensorRT implementation of YOLOv4
PyTorch ,ONNX and TensorRT implementation of YOLOv4
An easier way to build neural search on the cloud
Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
This repo contains the pytorch implementation for Dynamic Concept Learner (accepted by ICLR 2021).
DCL-PyTorch Pytorch implementation for the Dynamic Concept Learner (DCL). More details can be found at the project page. Framework Grounding Physical
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
Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
RecSim NG, a probabilistic platform for multi-agent recommender systems simulation. RecSimNG is a scalable, modular, differentiable simulator implemented in Edward2 and TensorFlow. It offers: a powerful, general probabilistic programming language for agent-behavior specification;
A small demonstration of using WebDataset with ImageNet and PyTorch Lightning
A small demonstration of using WebDataset with ImageNet and PyTorch Lightning
Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)
Fast and Flexible Temporal Point Processes with Triangular Maps This repository includes a reference implementation of the algorithms described in "Fa
Pytorch implementation of CoCon: A Self-Supervised Approach for Controlled Text Generation
COCON_ICLR2021 This is our Pytorch implementation of COCON. CoCon: A Self-Supervised Approach for Controlled Text Generation (ICLR 2021) Alvin Chan, Y
StyleMapGAN - Official PyTorch Implementation
StyleMapGAN - Official PyTorch Implementation StyleMapGAN: Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing Hyunsu Kim, Yunj
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
[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
TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.
TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost
A PyTorch Implementation of the paper - Choi, Woosung, et al. "Investigating u-nets with various intermediate blocks for spectrogram-based singing voice separation." 21th International Society for Music Information Retrieval Conference, ISMIR. 2020.
Investigating U-NETS With Various Intermediate Blocks For Spectrogram-based Singing Voice Separation A Pytorch Implementation of the paper "Investigat
[CVPR 2021] MiVOS - Scribble to Mask module
MiVOS (CVPR 2021) - Scribble To Mask Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] A simplistic network that turns scri
Official Pytorch implementation of "Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video", CVPR 2021
TCMR: Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video Qualtitative result Paper teaser video Introduction This r
SNE-RoadSeg in PyTorch, ECCV 2020
SNE-RoadSeg Introduction This is the official PyTorch implementation of SNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentati
PyTorch implementation of GLOM
GLOM PyTorch implementation of GLOM, Geoffrey Hinton's new idea that integrates concepts from neural fields, top-down-bottom-up processing, and attent
Semi-supervised Video Deraining with Dynamical Rain Generator (CVPR, 2021, Pytorch)
S2VD Semi-supervised Video Deraining with Dynamical Rain Generator (CVPR, 2021) Requirements and Dependencies Ubuntu 16.04, cuda 10.0 Python 3.6.10, P
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.
🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools
🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.
Documentation: https://mmgeneration.readthedocs.io/ Introduction English | 简体中文 MMGeneration is a powerful toolkit for generative models, especially f
This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.
Lite-HRNet: A Lightweight High-Resolution Network Introduction This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution
This repository contains a pytorch implementation of "StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision".
StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision | Project Page | Paper | This repository contains a pytorch implementation of "St
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
[TIP2020] Adaptive Graph Representation Learning for Video Person Re-identification
Introduction This is the PyTorch implementation for Adaptive Graph Representation Learning for Video Person Re-identification. Get started git clone h
KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.
Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par
PyTorch code for the paper "FIERY: Future Instance Segmentation in Bird's-Eye view from Surround Monocular Cameras"
FIERY This is the PyTorch implementation for inference and training of the future prediction bird's-eye view network as described in: FIERY: Future In
PyTorch implementation of the end-to-end coreference resolution model with different higher-order inference methods.
End-to-End Coreference Resolution with Different Higher-Order Inference Methods This repository contains the implementation of the paper: Revealing th
The official pytorch implemention of the CVPR paper "Temporal Modulation Network for Controllable Space-Time Video Super-Resolution".
This is the official PyTorch implementation of TMNet in the CVPR 2021 paper "Temporal Modulation Network for Controllable Space-Time VideoSuper-Resolu
Pytorch implementation for M^3L
Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification (CVPR 2021) Introduction This is the Py
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
BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation
BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation This is a demo implementation of BYOL for Audio (BYOL-A), a self-sup
Pytorch Implementation of LNSNet for Superpixel Segmentation
LNSNet Overview Official implementation of Learning the Superpixel in a Non-iterative and Lifelong Manner (CVPR'21) Learning Strategy The proposed LNS
PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos
PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-based API design, PyKale enforces standardization and minimalism, via reusing existing resources, reducing repetitions and redundancy, and recycling learning models across areas.
Reimplementation of the paper `Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words? (ACL2020)`
Human Attention for Text Classification Re-implementation of the paper Human Attention Maps for Text Classification: Do Humans and Neural Networks Foc
codes for Image Inpainting with External-internal Learning and Monochromic Bottleneck
Image Inpainting with External-internal Learning and Monochromic Bottleneck This repository is for the CVPR 2021 paper: 'Image Inpainting with Externa
Code for "Learning the Best Pooling Strategy for Visual Semantic Embedding", CVPR 2021
Learning the Best Pooling Strategy for Visual Semantic Embedding Official PyTorch implementation of the paper Learning the Best Pooling Strategy for V
This is the pytorch re-implementation of the IterNorm
IterNorm-pytorch Pytorch reimplementation of the IterNorm methods, which is described in the following paper: Iterative Normalization: Beyond Standard
code for paper "Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?"
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Code for paper: Does Unsupervised Architecture Representation
The official PyTorch implementation of the paper: *Xili Dai, Xiaojun Yuan, Haigang Gong, Yi Ma. "Fully Convolutional Line Parsing." *.
F-Clip — Fully Convolutional Line Parsing This repository contains the official PyTorch implementation of the paper: *Xili Dai, Xiaojun Yuan, Haigang
Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(2021) paper
ImageNet-21K Pretraining for the Masses Paper | Pretrained models Official PyTorch Implementation Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelni
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