2913 Repositories
Python SimSiam-pytorch Libraries
Implementation of RegretNet with Pytorch
Dependencies are Python 3, a recent PyTorch, numpy/scipy, tqdm, future and tensorboard. Plotting with Matplotlib. Implementation of the neural network
PyTorch implementation of MSBG hearing loss model and MBSTOI intelligibility metric
PyTorch implementation of MSBG hearing loss model and MBSTOI intelligibility metric This repository contains the implementation of MSBG hearing loss m
A little Python application to auto tag your photos with the power of machine learning.
Tag Machine A little Python application to auto tag your photos with the power of machine learning. Report a bug or request a feature Table of Content
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
Enformer - Pytorch (wip) Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch. The original tensorflow
Trains an OpenNMT PyTorch model and SentencePiece tokenizer.
Trains an OpenNMT PyTorch model and SentencePiece tokenizer. Designed for use with Argos Translate and LibreTranslate.
Official PyTorch implementation of "Improving Face Recognition with Large AgeGaps by Learning to Distinguish Children" (BMVC 2021)
Inter-Prototype (BMVC 2021): Official Project Webpage This repository provides the official PyTorch implementation of the following paper: Improving F
Official implementation of "Learning Proposals for Practical Energy-Based Regression", 2021.
ebms_proposals Official implementation (PyTorch) of the paper: Learning Proposals for Practical Energy-Based Regression, 2021 [arXiv] [project]. Fredr
Segmentation models with pretrained backbones. PyTorch.
Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to
PyTorch framework for Deep Learning research and development.
Accelerated DL & RL PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentati
95.47% on CIFAR10 with PyTorch
Train CIFAR10 with PyTorch I'm playing with PyTorch on the CIFAR10 dataset. Prerequisites Python 3.6+ PyTorch 1.0+ Training # Start training with: py
Classifying cat and dog images using Kaggle dataset
PyTorch Image Classification Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to
PyTorch implementation of Convolutional Neural Fabrics http://arxiv.org/abs/1606.02492
PyTorch implementation of Convolutional Neural Fabrics arxiv:1606.02492 There are some minor differences: The raw image is first convolved, to obtain
Very Deep Convolutional Networks for Large-Scale Image Recognition
pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo
an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I
PyTorch and Tensorflow functional model definitions
functional-zoo Model definitions and pretrained weights for PyTorch and Tensorflow PyTorch, unlike lua torch, has autograd in it's core, so using modu
PyTorch code for the "Deep Neural Networks with Box Convolutions" paper
Box Convolution Layer for ConvNets Single-box-conv network (from `examples/mnist.py`) learns patterns on MNIST What This Is This is a PyTorch implemen
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models
octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f
A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
LegoNet This code is the implementation of ICML2019 paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters Run python train.py You c
PyTorch implementation of the implicit Q-learning algorithm (IQL)
Implicit-Q-Learning (IQL) PyTorch implementation of the implicit Q-learning algorithm IQL (Paper) Currently only implemented for online learning. Offl
Official PyTorch code for the paper: "Point-Based Modeling of Human Clothing" (ICCV 2021)
Point-Based Modeling of Human Clothing Paper | Project page | Video This is an official PyTorch code repository of the paper "Point-Based Modeling of
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
Adaptive wavelets Wavelets which adapt given data (and optionally a pre-trained model). This yields models which are faster, more compressible, and mo
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
Unsupervised Depth Completion with Calibrated Backprojection Layers PyTorch implementation of Unsupervised Depth Completion with Calibrated Backprojec
Official PyTorch implementation of "Improving Face Recognition with Large AgeGaps by Learning to Distinguish Children" (BMVC 2021)
Inter-Prototype (BMVC 2021): Official Project Webpage This repository provides the official PyTorch implementation of the following paper: Improving F
A lightweight library to compare different PyTorch implementations of the same network architecture.
TorchBug is a lightweight library designed to compare two PyTorch implementations of the same network architecture. It allows you to count, and compar
PyTorch to TensorFlow Lite converter
PyTorch to TensorFlow Lite converter
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
High-fidelity performance metrics for generative models in PyTorch
High-fidelity performance metrics for generative models in PyTorch
Pytorch implementation of the paper Progressive Growing of Points with Tree-structured Generators (BMVC 2021)
PGpoints Pytorch implementation of the paper Progressive Growing of Points with Tree-structured Generators (BMVC 2021) Hyeontae Son, Young Min Kim Pre
Yolov3 pytorch implementation
YOLOV3 Pytorch实现 在bubbliiing大佬代码的基础上进行了修改,添加了部分注释。 预训练模型 预训练模型来源于bubbliiing。 链接:https://pan.baidu.com/s/1ncREw6Na9ycZptdxiVMApw 提取码:appk 训练自己的数据集 按照VO
使用yolov5训练自己数据集(详细过程)并通过flask部署
使用yolov5训练自己的数据集(详细过程)并通过flask部署 依赖库 torch torchvision numpy opencv-python lxml tqdm flask pillow tensorboard matplotlib pycocotools Windows,请使用 pycoc
Network Enhancement implementation in pytorch
network_enahncement_pytorch Network Enhancement implementation in pytorch Research paper Network Enhancement: a general method to denoise weighted bio
The repository offers the official implementation of our BMVC 2021 paper in PyTorch.
CrossMLP Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation Bin Ren1, Hao Tang2, Nicu Sebe1. 1University of Trento, Italy, 2ETH, Switzerla
pytorch implementation of ABC : Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
ABC:Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning, NeurIPS 2021 pytorch implementation of ABC : Auxiliary Balanced Class
PyTorch code of my WACV 2022 paper Improving Model Generalization by Agreement of Learned Representations from Data Augmentation
Improving Model Generalization by Agreement of Learned Representations from Data Augmentation (WACV 2022) Paper ArXiv Why it matters? When data augmen
A PyTorch-centric hybrid classical-quantum machine learning framework
torchquantum A PyTorch-centric hybrid classical-quantum dynamic neural networks framework. News Add a simple example script using quantum gates to do
This repository contains all source code, pre-trained models related to the paper "An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator"
An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o
NeurIPS'21: Probabilistic Margins for Instance Reweighting in Adversarial Training (Pytorch implementation).
source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training
Recognition of 38 speech commands in russian. Based on Yandex Cup 2021 ML Challenge: ASR
Speech_38_ru_commands Recognition of 38 speech commands in russian. Based on Yandex Cup 2021 ML Challenge: ASR Программа умеет распознавать 38 ключевы
PyTorch version implementation of DORN
DORN_PyTorch This is a PyTorch version implementation of DORN Reference H. Fu, M. Gong, C. Wang, K. Batmanghelich and D. Tao: Deep Ordinal Regression
[BMVC 2021] Official PyTorch Implementation of Self-supervised learning of Image Scale and Orientation Estimation
Self-Supervised Learning of Image Scale and Orientation Estimation (BMVC 2021) This is the official implementation of the paper "Self-Supervised Learn
The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou, Quan Cui, Xiu-Shen Wei*, Zhao-Min Chen This repo
Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets" (ECCV 2020 Spotlight)
Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (
Reverse engineer your pytorch vision models, in style
🔍 Rover Reverse engineer your CNNs, in style Rover will help you break down your CNN and visualize the features from within the model. No need to wri
A Python/Pytorch app for easily synthesising human voices
Voice Cloning App A Python/Pytorch app for easily synthesising human voices Documentation Discord Server Video guide Voice Sharing Hub FAQ's System Re
A bunch of random PyTorch models using PyTorch's C++ frontend
PyTorch Deep Learning Models using the C++ frontend Gettting started Clone the repo 1. https://github.com/mrdvince/pytorchcpp 2. cd fashionmnist or
A Word Level Transformer layer based on PyTorch and 🤗 Transformers.
Transformer Embedder A Word Level Transformer layer based on PyTorch and 🤗 Transformers. How to use Install the library from PyPI: pip install transf
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do
a reimplementation of Holistically-Nested Edge Detection in PyTorch
pytorch-hed This is a personal reimplementation of Holistically-Nested Edge Detection [1] using PyTorch. Should you be making use of this work, please
a reimplementation of LiteFlowNet in PyTorch that matches the official Caffe version
pytorch-liteflownet This is a personal reimplementation of LiteFlowNet [1] using PyTorch. Should you be making use of this work, please cite the paper
a reimplementation of UnFlow in PyTorch that matches the official TensorFlow version
pytorch-unflow This is a personal reimplementation of UnFlow [1] using PyTorch. Should you be making use of this work, please cite the paper according
an implementation of softmax splatting for differentiable forward warping using PyTorch
softmax-splatting This is a reference implementation of the softmax splatting operator, which has been proposed in Softmax Splatting for Video Frame I
an implementation of 3D Ken Burns Effect from a Single Image using PyTorch
3d-ken-burns This is a reference implementation of 3D Ken Burns Effect from a Single Image [1] using PyTorch. Given a single input image, it animates
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
LWCC: A LightWeight Crowd Counting library for Python LWCC is a lightweight crowd counting framework for Python. It wraps four state-of-the-art models
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
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI
Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
chitra What is chitra? chitra (चित्र) is a multi-functional library for full-stack Deep Learning. It simplifies Model Building, API development, and M
Differentiable scientific computing library
xitorch: differentiable scientific computing library xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely
Pytorch implementation of SimSiam Architecture
SimSiam-pytorch A simple pytorch implementation of Exploring Simple Siamese Representation Learning which is developed by Facebook AI Research (FAIR)
PyTorch implementation of SQN based on CloserLook3D's encoder
SQN_pytorch This repo is an implementation of Semantic Query Network (SQN) using CloserLook3D's encoder in Pytorch. For TensorFlow implementation, che
Deep learning library for solving differential equations and more
DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need
a pytorch implementation of auto-punctuation learned character by character
Learning Auto-Punctuation by Reading Engadget Articles Link to Other of my work 🌟 Deep Learning Notes: A collection of my notes going from basic mult
Deep Learning (with PyTorch)
Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
Official Pytorch implementation of the paper "Action-Conditioned 3D Human Motion Synthesis with Transformer VAE", ICCV 2021
ACTOR Official Pytorch implementation of the paper "Action-Conditioned 3D Human Motion Synthesis with Transformer VAE", ICCV 2021. Please visit our we
PyTorch implementation of the paper Ultra Fast Structure-aware Deep Lane Detection
PyTorch implementation of the paper Ultra Fast Structure-aware Deep Lane Detection
Chatbot with Pytorch, Python & Nextjs
Installation Instructions Make sure that you have Python 3, gcc, venv, and pip installed. Clone the repository $ git clone https://github.com/sahr
Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO)
V-MPO Simple code to demonstrate Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO) in Pyt
Pytorch implementation of paper "Learning Co-segmentation by Segment Swapping for Retrieval and Discovery"
SegSwap Pytorch implementation of paper "Learning Co-segmentation by Segment Swapping for Retrieval and Discovery" [PDF] [Project page] If our project
Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"
About this repository This repo contains an Pytorch implementation for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Netwo
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
PyTorch implementation of D2C: Diffuison-Decoding Models for Few-shot Conditional Generation.
D2C: Diffuison-Decoding Models for Few-shot Conditional Generation Project | Paper PyTorch implementation of D2C: Diffuison-Decoding Models for Few-sh
A PyTorch implementation of Implicit Q-Learning
IQL-PyTorch This repository houses a minimal PyTorch implementation of Implicit Q-Learning (IQL), an offline reinforcement learning algorithm, along w
Official PyTorch Implementation of Mask-aware IoU and maYOLACT Detector [BMVC2021]
The official implementation of Mask-aware IoU and maYOLACT detector. Our implementation is based on mmdetection. Mask-aware IoU for Anchor Assignment
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
Nest - A flexible tool for building and sharing deep learning modules
Nest - A flexible tool for building and sharing deep learning modules Nest is a flexible deep learning module manager, which aims at encouraging code
Pytorch and Torch testing code of CartoonGAN
CartoonGAN-Test-Pytorch-Torch Pytorch and Torch testing code of CartoonGAN [Chen et al., CVPR18]. With the released pretrained models by the authors,
pytorch implementation of "Contrastive Multiview Coding", "Momentum Contrast for Unsupervised Visual Representation Learning", and "Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination"
Unofficial implementation: MoCo: Momentum Contrast for Unsupervised Visual Representation Learning (Paper) InsDis: Unsupervised Feature Learning via N
Unofficial pytorch implementation of 'Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization'
pytorch-AdaIN This is an unofficial pytorch implementation of a paper, Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Hua
Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.
Vector AI is a framework designed to make the process of building production grade vector based applications as quickly and easily as possible. Create
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
BackgroundRemover lets you Remove Background from images and video with a simple command line interface
BackgroundRemover BackgroundRemover is a command line tool to remove background from video and image, made by nadermx to power https://BackgroundRemov
Flower - A Friendly Federated Learning Framework
Flower - A Friendly Federated Learning Framework Flower (flwr) is a framework for building federated learning systems. The design of Flower is based o
Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)
Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
labml.ai Deep Learning Paper Implementations This is a collection of simple PyTorch implementations of neural networks and related algorithms. These i
Official PyTorch implementation of paper: Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation (ICCV 2021 Oral Presentation)
SML (ICCV 2021, Oral) : Official Pytorch Implementation This repository provides the official PyTorch implementation of the following paper: Standardi
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
TorchCAM: class activation explorer Simple way to leverage the class-specific activation of convolutional layers in PyTorch. Quick Tour Setting your C
Pytorch implementation of MixNMatch
MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation [Paper] Yuheng Li, Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Le
Production First and Production Ready End-to-End Speech Recognition Toolkit
WeNet 中文版 Discussions | Docs | Papers | Runtime (x86) | Runtime (android) | Pretrained Models We share neural Net together. The main motivation of WeN
Vector Quantization, in Pytorch
Vector Quantization - Pytorch A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a
MutualGuide is a compact object detector specially designed for embedded devices
Introduction MutualGuide is a compact object detector specially designed for embedded devices. Comparing to existing detectors, this repo contains two
Compare neural networks by their feature similarity
PyTorch Model Compare A tiny package to compare two neural networks in PyTorch. There are many ways to compare two neural networks, but one robust and
Mengzi Pretrained Models
中文 | English Mengzi 尽管预训练语言模型在 NLP 的各个领域里得到了广泛的应用,但是其高昂的时间和算力成本依然是一个亟需解决的问题。这要求我们在一定的算力约束下,研发出各项指标更优的模型。 我们的目标不是追求更大的模型规模,而是轻量级但更强大,同时对部署和工业落地更友好的模型。
PyTorch code for DriveGAN: Towards a Controllable High-Quality Neural Simulation
PyTorch code for DriveGAN: Towards a Controllable High-Quality Neural Simulation
Official Pytorch implementation of "Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral)"
Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral): Official Project Webpage This repository provides the off
Building blocks for uncertainty-aware cycle consistency presented at NeurIPS'21.
UncertaintyAwareCycleConsistency This repository provides the building blocks and the API for the work presented in the NeurIPS'21 paper Robustness vi
pytorch bert intent classification and slot filling
pytorch_bert_intent_classification_and_slot_filling 基于pytorch的中文意图识别和槽位填充 说明 基本思路就是:分类+序列标注(命名实体识别)同时训练。 使用的预训练模型:hugging face上的chinese-bert-wwm-ext 依
The pytorch implementation of SOKD (BMVC2021).
Semi-Online Knowledge Distillation Implementations of SOKD. Requirements This repo was tested with Python 3.8, PyTorch 1.5.1, torchvision 0.6.1, CUDA
Pytorch implementation of the paper Time-series Generative Adversarial Networks
TimeGAN-pytorch Pytorch implementation of the paper Time-series Generative Adversarial Networks presented at NeurIPS'19. Jinsung Yoon, Daniel Jarrett