3096 Repositories
Python pytorch-benchmark Libraries
Complete system for facial identity system. Include one-shot model, database operation, features visualization, monitoring
Complete system for facial identity system. Include one-shot model, database operation, features visualization, monitoring
Automatically remove the mosaics in images and videos, or add mosaics to them.
Automatically remove the mosaics in images and videos, or add mosaics to them.
Almost State-of-the-art Text Generation library
Ps: we are adding transformer model soon Text Gen 🐐 Almost State-of-the-art Text Generation library Text gen is a python library that allow you build
Pytorch implementation of our paper under review -- 1xN Pattern for Pruning Convolutional Neural Networks
1xN Pattern for Pruning Convolutional Neural Networks (paper) . This is Pytorch re-implementation of "1xN Pattern for Pruning Convolutional Neural Net
Code of TIP2021 Paper《SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition》. We provide both MxNet and Pytorch versions.
SFace Code of TIP2021 Paper 《SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition》. We provide both MxNet, PyTorch and Jittor versi
AdvStyle - Official PyTorch Implementation
AdvStyle - Official PyTorch Implementation Paper | Supp Discovering Interpretable Latent Space Directions of GANs Beyond Binary Attributes. Huiting Ya
Ensembling Off-the-shelf Models for GAN Training
Vision-aided GAN video (3m) | website | paper Can the collective knowledge from a large bank of pretrained vision models be leveraged to improve GAN t
[AAAI 2022] Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding
[AAAI 2022] Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding Official Pytorch implementation of Negative Sample Matter
Reference code for the paper "Cross-Camera Convolutional Color Constancy" (ICCV 2021)
Cross-Camera Convolutional Color Constancy, ICCV 2021 (Oral) Mahmoud Afifi1,2, Jonathan T. Barron2, Chloe LeGendre2, Yun-Ta Tsai2, and Francois Bleibe
This is the official PyTorch implementation of the CVPR 2020 paper "TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting".
TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting Project Page | YouTube | Paper This is the official PyTorch implementation of the C
PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
Impersonator PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer an
PyTorch implementation for our paper Learning Character-Agnostic Motion for Motion Retargeting in 2D, SIGGRAPH 2019
Learning Character-Agnostic Motion for Motion Retargeting in 2D We provide PyTorch implementation for our paper Learning Character-Agnostic Motion for
User-friendly Voice Cloning Application
Multi-Language-RTVC stands for Multi-Language Real Time Voice Cloning and is a Voice Cloning Tool capable of transfering speaker-specific audio featur
Ensembling Off-the-shelf Models for GAN Training
Data-Efficient GANs with DiffAugment project | paper | datasets | video | slides Generated using only 100 images of Obama, grumpy cats, pandas, the Br
Chinese Named Entity Recognization (BiLSTM with PyTorch)
BiLSTM-CRF for Name Entity Recognition PyTorch version A PyTorch implemention of Bi-LSTM-CRF model for Chinese Named Entity Recognition. 使用 PyTorch 实现
Pytorch modules for paralel models with same architecture. Ideal for multi agent-based systems
WideLinears Pytorch parallel Neural Networks A package of pytorch modules for fast paralellization of separate deep neural networks. Ideal for agent-b
Label data using HuggingFace's transformers and automatically get a prediction service
Label Studio for Hugging Face's Transformers Website • Docs • Twitter • Join Slack Community Transfer learning for NLP models by annotating your textu
Using pytorch to implement unet network for liver image segmentation.
Using pytorch to implement unet network for liver image segmentation.
Flow is a computational framework for deep RL and control experiments for traffic microsimulation.
Flow Flow is a computational framework for deep RL and control experiments for traffic microsimulation. See our website for more information on the ap
A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization
University1652-Baseline [Paper] [Slide] [Explore Drone-view Data] [Explore Satellite-view Data] [Explore Street-view Data] [Video Sample] [中文介绍] This
UniSpeech - Large Scale Self-Supervised Learning for Speech
UniSpeech The family of UniSpeech: WavLM (arXiv): WavLM: Large-Scale Self-Supervised Pre-training for Full Stack Speech Processing UniSpeech (ICML 202
Official PyTorch implementation of SegFormer
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models
Fine-tuning scripts for evaluating transformer-based models on KLEJ benchmark.
The KLEJ Benchmark Baselines The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language und
Large-scale pretraining for dialogue
A State-of-the-Art Large-scale Pretrained Response Generation Model (DialoGPT) This repository contains the source code and trained model for a large-
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention
Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz
Fully featured implementation of Routing Transformer
Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the
PG-19 Language Modelling Benchmark
PG-19 Language Modelling Benchmark This repository contains the PG-19 language modeling benchmark. It includes a set of books extracted from the Proje
Awesome Treasure of Transformers Models Collection
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
Code for Crowd counting via unsupervised cross-domain feature adaptation.
CDFA-pytorch Code for Unsupervised crowd counting via cross-domain feature adaptation. Pre-trained models Google Drive Baidu Cloud : t4qc Environment
Reproduce partial features of DeePMD-kit using PyTorch.
DeePMD-kit on PyTorch For better understand DeePMD-kit, we implement its partial features using PyTorch and expose interface consuing descriptors. Tec
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Class-balanced-loss-pytorch Pytorch implementation of the paper Class-Balanced Loss Based on Effective Number of Samples presented at CVPR'19. Yin Cui
Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data
FTLNet_Pytorch Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data 1. Introduction This repo is an unofficial
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
Learning to Reweight Examples for Robust Deep Learning Unofficial PyTorch implementation of Learning to Reweight Examples for Robust Deep Learning. Th
A Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Training Data》
RangeLoss Pytorch This is a Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Trai
Learn the Deep Learning for Computer Vision in three steps: theory from base to SotA, code in PyTorch, and space-repetition with Anki
DeepCourse: Deep Learning for Computer Vision arthurdouillard.com/deepcourse/ This is a course I'm giving to the French engineering school EPITA each
Continual World is a benchmark for continual reinforcement learning
Continual World Continual World is a benchmark for continual reinforcement learning. It contains realistic robotic tasks which come from MetaWorld. Th
💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena
💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena.
A foreign language learning aid using a neural network to predict probability of translating foreign words
Langy Langy is a reading-focused foreign language learning aid orientated towards young children. Reading is an activity that every child knows. It is
A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.
Layer-wise Relevance Propagation (LRP) in PyTorch Basic unsupervised implementation of Layer-wise Relevance Propagation (Bach et al., Montavon et al.)
Convert onnx models to pytorch.
onnx2torch onnx2torch is an ONNX to PyTorch converter. Our converter: Is easy to use – Convert the ONNX model with the function call convert; Is easy
TRACER: Extreme Attention Guided Salient Object Tracing Network implementation in PyTorch
TRACER: Extreme Attention Guided Salient Object Tracing Network This paper was accepted at AAAI 2022 SA poster session. Datasets All datasets are avai
A PaddlePaddle version of Neural Renderer, refer to its PyTorch version
Neural 3D Mesh Renderer in PadddlePaddle A PaddlePaddle version of Neural Renderer, refer to its PyTorch version Install Run: pip install neural-rende
Official Pytorch implementation for Deep Contextual Video Compression, NeurIPS 2021
Introduction Official Pytorch implementation for Deep Contextual Video Compression, NeurIPS 2021 Prerequisites Python 3.8 and conda, get Conda CUDA 11
Pytorch implementation NORESQA A Framework for Speech Quality Assessment using Non-Matching References.
NORESQA: Speech Quality Assessment using Non-Matching References This is a Pytorch implementation for using NORESQA. It contains minimal code to predi
Library to enable Bayesian active learning in your research or labeling work.
Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components
🌾 PASTIS 🌾 Panoptic Agricultural Satellite TIme Series
🌾 PASTIS 🌾 Panoptic Agricultural Satellite TIme Series (optical and radar) The PASTIS Dataset Dataset presentation PASTIS is a benchmark dataset for
A configurable, tunable, and reproducible library for CTR prediction
FuxiCTR This repo is the community dev version of the official release at huawei-noah/benchmark/FuxiCTR. Click-through rate (CTR) prediction is an cri
AI4Good project for detecting waste in the environment
Detect waste AI4Good project for detecting waste in environment. www.detectwaste.ml. Our latest results were published in Waste Management journal in
AdamW optimizer for bfloat16 models in pytorch.
Image source AdamW optimizer for bfloat16 models in pytorch. Bfloat16 is currently an optimal tradeoff between range and relative error for deep netwo
This is a graphql api build using ariadne python that serves a graphql-endpoint at port 3002 to perform language translation and identification using deep learning in python pytorch.
Language Translation and Identification this machine/deep learning api that will be served as a graphql-api using ariadne, to perform the following ta
MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine Learning work with thousands of other users.
The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine
PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear
A python package simulating the quasi-2D pseudospin-1/2 Gross-Pitaevskii equation with NVIDIA GPU acceleration.
A python package simulating the quasi-2D pseudospin-1/2 Gross-Pitaevskii equation with NVIDIA GPU acceleration. Introduction spinor-gpe is high-level,
Evaluation toolkit of the informative tracking benchmark comprising 9 scenarios, 180 diverse videos, and new challenges.
Informative-tracking-benchmark Informative tracking benchmark (ITB) higher diversity. It contains 9 representative scenarios and 180 diverse videos. m
Hypernetwork-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels
Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels The implementation of Hypernet-Ensemble Le
CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability
This is the official repository of the paper: CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability A private copy of the
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Unofficial PyTorch Implementation of AHDRNet (CVPR 2019)
AHDRNet-PyTorch This is the PyTorch implementation of Attention-guided Network for Ghost-free High Dynamic Range Imaging (CVPR 2019). The official cod
A PyTorch implementation of deep-learning-based registration
DiffuseMorph Implementation A PyTorch implementation of deep-learning-based registration. Requirements OS : Ubuntu / Windows Python 3.6 PyTorch 1.4.0
Official PyTorch implementation of "Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks" (AAAI 2022)
Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks This is the code for reproducing the results of th
Official PyTorch implementation of the paper "Graph-based Generative Face Anonymisation with Pose Preservation" in ICIAP 2021
Contents AnonyGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evaluation Acknowledgments Citat
PyTorch implementation of normalizing flow models
PyTorch implementation of normalizing flow models
(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"
(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"
A PyTorch library and evaluation platform for end-to-end compression research
CompressAI CompressAI (compress-ay) is a PyTorch library and evaluation platform for end-to-end compression research. CompressAI currently provides: c
Mmdetection3d Noted - MMDetection3D is an open source object detection toolbox based on PyTorch
MMDetection3D is an open source object detection toolbox based on PyTorch
Users can free try their models on SIDD dataset based on this code
SIDD benchmark 1 Train python train.py If you want to train your network, just modify the yaml in the options folder. 2 Validation python validation.p
PyTorch implementation of a collections of scalable Video Transformer Benchmarks.
PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle
Continuous Augmented Positional Embeddings (CAPE) implementation for PyTorch
PyTorch implementation of Continuous Augmented Positional Embeddings (CAPE), by Likhomanenko et al. Enhance your Transformer positional embeddings with easy-to-use augmentations!
A python code to convert Keras pre-trained weights to Pytorch version
Weights_Keras_2_Pytorch 最近想在Pytorch项目里使用一下谷歌的NIMA,但是发现没有预训练好的pytorch权重,于是整理了一下将Keras预训练权重转为Pytorch的代码,目前是支持Keras的Conv2D, Dense, DepthwiseConv2D, Batch
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required.
NLP tool to extract emotional phrase from tweets 🤩
Emotional phrase extractor Extract phrase in the given text that is used to express the sentiment. Capturing sentiment in language is important in the
The Pytorch implementation for "Video-Text Pre-training with Learned Regions"
Region_Learner The Pytorch implementation for "Video-Text Pre-training with Learned Regions" (arxiv) We are still cleaning up the code further and pre
[NeurIPS 2021]: Are Transformers More Robust Than CNNs? (Pytorch implementation & checkpoints)
Are Transformers More Robust Than CNNs? Pytorch implementation for NeurIPS 2021 Paper: Are Transformers More Robust Than CNNs? Our implementation is b
FLSim a flexible, standalone library written in PyTorch that simulates FL settings with a minimal, easy-to-use API
Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such as vision and text.
Codes for CyGen, the novel generative modeling framework proposed in "On the Generative Utility of Cyclic Conditionals" (NeurIPS-21)
On the Generative Utility of Cyclic Conditionals This repository is the official implementation of "On the Generative Utility of Cyclic Conditionals"
Autoregressive Models in PyTorch.
Autoregressive This repository contains all the necessary PyTorch code, tailored to my presentation, to train and generate data from WaveNet-like auto
A modular PyTorch library for optical flow estimation using neural networks
A modular PyTorch library for optical flow estimation using neural networks
Re-implememtation of MAE (Masked Autoencoders Are Scalable Vision Learners) using PyTorch.
mae-repo PyTorch re-implememtation of "masked autoencoders are scalable vision learners". In this repo, it heavily borrows codes from codebase https:/
This repo contains the source code and a benchmark for predicting user's utilities with Machine Learning techniques for Computational Persuasion
Machine Learning for Argument-Based Computational Persuasion This repo contains the source code and a benchmark for predicting user's utilities with M
Official implementation of "A Shared Representation for Photorealistic Driving Simulators" in PyTorch.
A Shared Representation for Photorealistic Driving Simulators The official code for the paper: "A Shared Representation for Photorealistic Driving Sim
2D Human Pose estimation using transformers. Implementation in Pytorch
PE-former: Pose Estimation Transformer Vision transformer architectures perform very well for image classification tasks. Efforts to solve more challe
Riemann Noise Injection With PyTorch
Riemann Noise Injection - PyTorch A module for modeling GAN noise injection based on Riemann geometry, as described in Ruili Feng, Deli Zhao, and Zhen
Continuously update some NLP practice based on different tasks.
NLP_practice We will continuously update some NLP practice based on different tasks. prerequisites Software pytorch = 1.10 torchtext = 0.11.0 sklear
SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.
SOLO: Segmenting Objects by Locations This project hosts the code for implementing the SOLO algorithms for instance segmentation. SOLO: Segmenting Obj
R3Det based on mmdet 2.19.0
R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object Installation # install mmdetection first if you haven't installed it
Supplemental learning materials for "Fourier Feature Networks and Neural Volume Rendering"
Fourier Feature Networks and Neural Volume Rendering This repository is a companion to a lecture given at the University of Cambridge Engineering Depa
Unofficial PyTorch implementation of TokenLearner by Google AI
tokenlearner-pytorch Unofficial PyTorch implementation of TokenLearner by Ryoo et al. from Google AI (abs, pdf) Installation You can install TokenLear
Implementation of "Large Steps in Inverse Rendering of Geometry"
Large Steps in Inverse Rendering of Geometry ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia), December 2021. Baptiste Nicolet · Alec Jacob
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce (EMNLP Founding 2021)
Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor
PyTorch implementation of our paper: "Artistic Style Transfer with Internal-external Learning and Contrastive Learning"
Artistic Style Transfer with Internal-external Learning and Contrastive Learning This is the official PyTorch implementation of our paper: "Artistic S
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
Meta-Weight-Net NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Official Pytorch implementation for noisy labels). The
[NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS).
A Strong Single-Stage Baseline for Long-Tailed Problems This project provides a strong single-stage baseline for Long-Tailed Classification (under Ima
[ICLR 2021 Spotlight] Pytorch implementation for "Long-tailed Recognition by Routing Diverse Distribution-Aware Experts."
RIDE: Long-tailed Recognition by Routing Diverse Distribution-Aware Experts. by Xudong Wang, Long Lian, Zhongqi Miao, Ziwei Liu and Stella X. Yu at UC
Official PyTorch implementation of RIO
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection Figure 1: Our proposed Resampling at image-level and obect-
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
WebDataset WebDataset is a PyTorch Dataset (IterableDataset) implementation providing efficient access to datasets stored in POSIX tar archives and us
Torchrecipes provides a set of reproduci-able, re-usable, ready-to-run RECIPES for training different types of models, across multiple domains, on PyTorch Lightning.
Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reproducibility, and infrastructure to guarantee correctness, efficiency, and interoperability.
State-of-the-art NLP through transformer models in a modular design and consistent APIs.
Trapper (Transformers wRAPPER) Trapper is an NLP library that aims to make it easier to train transformer based models on downstream tasks. It wraps h
Pytorch Implementations of large number classical backbone CNNs, data enhancement, torch loss, attention, visualization and some common algorithms.
Torch-template-for-deep-learning Pytorch implementations of some **classical backbone CNNs, data enhancement, torch loss, attention, visualization and
Official PyTorch Implementation of GAN-Supervised Dense Visual Alignment
GAN-Supervised Dense Visual Alignment — Official PyTorch Implementation Paper | Project Page | Video This repo contains training, evaluation and visua