1705 Repositories
Python Swin-Transformer-Semantic-Segmentation Libraries
Detect textlines in document images
Textline Detection Detect textlines in document images Introduction This tool performs border, region and textline detection from document image data
Adaptive Attention Span for Reinforcement Learning
Adaptive Transformers in RL Official implementation of Adaptive Transformers in RL In this work we replicate several results from Stabilizing Transfor
git《Commonsense Knowledge Base Completion with Structural and Semantic Context》(AAAI 2020) GitHub: [fig1]
Commonsense Knowledge Base Completion with Structural and Semantic Context Code for the paper Commonsense Knowledge Base Completion with Structural an
Code for SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics (ACL'2020).
SentiBERT Code for SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics (ACL'2020). https://arxiv.org/abs/20
Transformer Tracking (CVPR2021)
TransT - Transformer Tracking [CVPR2021] Official implementation of the TransT (CVPR2021) , including training code and trained models. We are revisin
[CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion
[CVPR 2021] Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion
Open source code for Paper "A Co-Interactive Transformer for Joint Slot Filling and Intent Detection"
A Co-Interactive Transformer for Joint Slot Filling and Intent Detection This repository contains the PyTorch implementation of the paper: A Co-Intera
Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
TTNet-Pytorch The implementation for the paper "TTNet: Real-time temporal and spatial video analysis of table tennis" An introduction of the project c
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
OpenMMLab Detection Toolbox and Benchmark
MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.
Model parallel transformers in Jax and Haiku
Mesh Transformer Jax A haiku library using the new(ly documented) xmap operator in Jax for model parallelism of transformers. See enwik8_example.py fo
CTC segmentation python package
CTC segmentation CTC segmentation can be used to find utterances alignments within large audio files. This repository contains the ctc-segmentation py
[CVPR2021 Oral] End-to-End Video Instance Segmentation with Transformers
VisTR: End-to-End Video Instance Segmentation with Transformers This is the official implementation of the VisTR paper: Installation We provide instru
This is the code for HOI Transformer
HOI Transformer Code for CVPR 2021 accepted paper End-to-End Human Object Interaction Detection with HOI Transformer. Reproduction We recomend you to
An official implementation of "SFNet: Learning Object-aware Semantic Correspondence" (CVPR 2019, TPAMI 2020) in PyTorch.
PyTorch implementation of SFNet This is the implementation of the paper "SFNet: Learning Object-aware Semantic Correspondence". For more information,
CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation
CoTr: Efficient 3D Medical Image Segmentation by bridging CNN and Transformer This is the official pytorch implementation of the CoTr: Paper: CoTr: Ef
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP
This repo provides the official code for TransBTS: Multimodal Brain Tumor Segmentation Using Transformer (https://arxiv.org/pdf/2103.04430.pdf).
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer This repo is the official implementation for TransBTS: Multimodal Brain Tumor Segmenta
本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料,该资料目前包含 自然语言处理各领域的 面试题积累。
【关于 NLP】那些你不知道的事 作者:杨夕、芙蕖、李玲、陈海顺、twilight、LeoLRH、JimmyDU、艾春辉、张永泰、金金金 介绍 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料,该资料目前包含 自然语言处理各领域的 面试题积累。 目录架构 一、【
Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper
Data Augmentation using Pre-trained Transformer Models Code associated with the Data Augmentation using Pre-trained Transformer Models paper Code cont
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125
Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc
Image augmentation for machine learning experiments.
imgaug This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much lar
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. Flair is: A powerful NLP library. Flair allo
Python histogram library - histograms as updateable, fully semantic objects with visualization tools. [P]ython [HYST]ograms.
physt P(i/y)thon h(i/y)stograms. Inspired (and based on) numpy.histogram, but designed for humans(TM) on steroids(TM). The goal is to unify different
Gluon CV Toolkit
Gluon CV Toolkit | Installation | Documentation | Tutorials | GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c
Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention
E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"
Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo
Implementation of SETR model, Original paper: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.
SETR - Pytorch Since the original paper (Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.) has no official
A multi-entity Transformer for multi-agent spatiotemporal modeling.
baller2vec This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec: A Multi-Entity Transformer For Multi-Agent Spatiotempor
This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
TransUNet This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Usage
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals.
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals This repo contains the Pytorch implementation of our paper: Unsupervised Seman
Transfer SemanticKITTI labeles into other dataset/sensor formats.
LiDAR-Transfer Transfer SemanticKITTI labeles into other dataset/sensor formats. Content Convert datasets (NUSCENES, FORD, NCLT) to KITTI format Minim
Knowledge Management for Humans using Machine Learning & Tags
HyperTag HyperTag helps humans intuitively express how they think about their files using tags and machine learning.
Reviving Iterative Training with Mask Guidance for Interactive Segmentation
This repository provides the source code for training and testing state-of-the-art click-based interactive segmentation models with the official PyTorch implementation
Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.
Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch
Puzzle-CAM: Improved localization via matching partial and full features.
Puzzle-CAM The official implementation of "Puzzle-CAM: Improved localization via matching partial and full features".
Knowledge Management for Humans using Machine Learning & Tags
HyperTag helps humans intuitively express how they think about their files using tags and machine learning. Represent how you think using tags. Find what you look for using semantic search for your text documents (yes, even PDF's) and images.
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag
Unsupervised text tokenizer focused on computational efficiency
YouTokenToMe YouTokenToMe is an unsupervised text tokenizer focused on computational efficiency. It currently implements fast Byte Pair Encoding (BPE)
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.
pySBD: Python Sentence Boundary Disambiguation (SBD) pySBD - python Sentence Boundary Disambiguation (SBD) - is a rule-based sentence boundary detecti
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
T5: Text-To-Text Transfer Transformer The t5 library serves primarily as code for reproducing the experiments in Exploring the Limits of Transfer Lear
:mag: End-to-End Framework for building natural language search interfaces to data by utilizing Transformers and the State-of-the-Art of NLP. Supporting DPR, Elasticsearch, HuggingFace’s Modelhub and much more!
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
An easier way to build neural search on the cloud
An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models
Unsupervised text tokenizer for Neural Network-based text generation.
SentencePiece SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabu
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
A Python library for audio feature extraction, classification, segmentation and applications This doc contains general info. Click here for the comple
TransGAN: Two Transformers Can Make One Strong GAN
[Preprint] "TransGAN: Two Transformers Can Make One Strong GAN", Yifan Jiang, Shiyu Chang, Zhangyang Wang
Official implementation of the ICLR 2021 paper
You Only Need Adversarial Supervision for Semantic Image Synthesis Official PyTorch implementation of the ICLR 2021 paper "You Only Need Adversarial S
Implementation of TabTransformer, attention network for tabular data, in Pytorch
Tab Transformer Implementation of Tab Transformer, attention network for tabular data, in Pytorch. This simple architecture came within a hair's bread
Exploring Cross-Image Pixel Contrast for Semantic Segmentation
Exploring Cross-Image Pixel Contrast for Semantic Segmentation Exploring Cross-Image Pixel Contrast for Semantic Segmentation, Wenguan Wang, Tianfei Z
A vision library for performing sliced inference on large images/small objects
SAHI: Slicing Aided Hyper Inference A vision library for performing sliced inference on large images/small objects Overview Object detection and insta
Code for "Learning to Segment Rigid Motions from Two Frames".
rigidmask Code for "Learning to Segment Rigid Motions from Two Frames". ** This is a partial release with inference and evaluation code.
Authors implementation of LieTransformer: Equivariant Self-Attention for Lie Groups
LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant self-at
Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation
Unseen Object Clustering: Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation Introduction In this work, we propose a new method
the code used for the preprint Embedding-based Instance Segmentation of Microscopy Images.
EmbedSeg Introduction This repository hosts the version of the code used for the preprint Embedding-based Instance Segmentation of Microscopy Images.
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
Implementation of the paper NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting.
Non-AR Spatial-Temporal Transformer Introduction Implementation of the paper NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series For
GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training Code and model from our AAAI 2021 paper
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag
Unsupervised text tokenizer focused on computational efficiency
YouTokenToMe YouTokenToMe is an unsupervised text tokenizer focused on computational efficiency. It currently implements fast Byte Pair Encoding (BPE)
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.
pySBD: Python Sentence Boundary Disambiguation (SBD) pySBD - python Sentence Boundary Disambiguation (SBD) - is a rule-based sentence boundary detecti
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
T5: Text-To-Text Transfer Transformer The t5 library serves primarily as code for reproducing the experiments in Exploring the Limits of Transfer Lear
:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...
Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran
An easier way to build neural search on the cloud
An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models
Unsupervised text tokenizer for Neural Network-based text generation.
SentencePiece SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabu
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
Extract embedded metadata from HTML markup
extruct extruct is a library for extracting embedded metadata from HTML markup. Currently, extruct supports: W3C's HTML Microdata embedded JSON-LD Mic
Awesome Django Markdown Editor, supported for Bootstrap & Semantic-UI
martor Martor is a Markdown Editor plugin for Django, supported for Bootstrap & Semantic-UI. Features Live Preview Integrated with Ace Editor Supporte
NLP Core Library and Model Zoo based on PaddlePaddle 2.0
PaddleNLP 2.0拥有丰富的模型库、简洁易用的API与高性能的分布式训练的能力,旨在为飞桨开发者提升文本建模效率,并提供基于PaddlePaddle 2.0的NLP领域最佳实践。
Implementation of Feedback Transformer in Pytorch
Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce
Transformer-based Text Auto-encoder (T-TA) using TensorFlow 2.
T-TA (Transformer-based Text Auto-encoder) This repository contains codes for Transformer-based Text Auto-encoder (T-TA, paper: Fast and Accurate Deep
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
DALL-E in Pytorch Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the ge
YolactEdge: Real-time Instance Segmentation on the Edge
YolactEdge, the first competitive instance segmentation approach that runs on small edge devices at real-time speeds. Specifically, YolactEdge runs at up to 30.8 FPS on a Jetson AGX Xavier (and 172.7 FPS on an RTX 2080 Ti) with a ResNet-101 backbone on 550x550 resolution images.
Implementation of Bottleneck Transformer in Pytorch
Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms
Jittor implementation of PCT:Point Cloud Transformer
PCT: Point Cloud Transformer This is a Jittor implementation of PCT: Point Cloud Transformer.
Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
Trankit: A Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing Trankit is a light-weight Transformer-based Pyth
Multiple-Object Tracking with Transformer
TransTrack: Multiple-Object Tracking with Transformer Introduction TransTrack: Multiple-Object Tracking with Transformer Models Training data Training
Chinese NewsTitle Generation Project by GPT2.带有超级详细注释的中文GPT2新闻标题生成项目。
GPT2-NewsTitle 带有超详细注释的GPT2新闻标题生成项目 UpDate 01.02.2021 从网上收集数据,将清华新闻数据、搜狗新闻数据等新闻数据集,以及开源的一些摘要数据进行整理清洗,构建一个较完善的中文摘要数据集。 数据集清洗时,仅进行了简单地规则清洗。
This repository is an unoffical PyTorch implementation of Medical segmentation in 3D and 2D.
Pytorch Medical Segmentation Read Chinese Introduction:Here! Recent Updates 2021.1.8 The train and test codes are released. 2021.2.6 A bug in dice was
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin
Implementation of the Point Transformer layer, in Pytorch
Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed
Graph Transformer Architecture. Source code for
Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres
Big Bird: Transformers for Longer Sequences
BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
SWA Object Detection
SWA Object Detection This project hosts the scripts for training SWA object detectors, as presented in our paper: @article{zhang2020swa, title={SWA
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Segmentation Transformer Implementation of Segmentation Transformer in PyTorch, a new model to achieve SOTA in semantic segmentation while using trans
Explainability for Vision Transformers (in PyTorch)
Explainability for Vision Transformers (in PyTorch) This repository implements methods for explainability in Vision Transformers
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch.
SE3 Transformer - Pytorch Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. May be needed for replicating Alphafold2 resu
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch
Lie Transformer - Pytorch (wip) Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch. Only the SE3 version will be present in thi
Pytorch implementation of PCT: Point Cloud Transformer
PCT: Point Cloud Transformer This is a Pytorch implementation of PCT: Point Cloud Transformer.
: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
PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)
PyTorch implementation of Conformer: Convolution-augmented Transformer for Speech Recognition. Transformer models are good at capturing content-based
Graph neural network message passing reframed as a Transformer with local attention
Adjacent Attention Network An implementation of a simple transformer that is equivalent to graph neural network where the message passing is done with
Code for our method RePRI for Few-Shot Segmentation. Paper at http://arxiv.org/abs/2012.06166
Region Proportion Regularized Inference (RePRI) for Few-Shot Segmentation In this repo, we provide the code for our paper : "Few-Shot Segmentation Wit
Chinese segmentation library
What is loso? loso is a Chinese segmentation system written in Python. It was developed by Victor Lin ([email protected]) for Plurk Inc. Copyright &
pkuseg多领域中文分词工具; The pkuseg toolkit for multi-domain Chinese word segmentation
pkuseg:一个多领域中文分词工具包 (English Version) pkuseg 是基于论文[Luo et. al, 2019]的工具包。其简单易用,支持细分领域分词,有效提升了分词准确度。 目录 主要亮点 编译和安装 各类分词工具包的性能对比 使用方式 论文引用 作者 常见问题及解答 主要