1085 Open source projects that are alternatives of or similar to DocuNet

🍀 Pytorch Implementation of RandLA-Net (https://arxiv.org/abs/1911.11236)

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

Official Pytorch Code of KiU-Net for Image Segmentation - MICCAI 2020 (Oral)

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

Pytorch implementation of Paper by Google Research - Representation Learning for Information Extraction from Form-like Documents.

TFslim based semantic segmentation models, modular&extensible boutique design

CRF-RNN PyTorch version http://crfasrnn.torr.vision

An opensource lib. for vehicle vision applications (written by MATLAB), lane marking detection, road segmentation

从模型训练到部署，实战知识图谱(Knowledge Graph)&自然语言处理(NLP)。涉及 Tensorflow, Bert+Bi-LSTM+CRF,Neo4j等 涵盖 Named Entity Recognition,Text Classify,Information Extraction,Relation Extraction 等任务。

Attention Guided Graph Convolutional Networks for Relation Extraction (authors' PyTorch implementation for the ACL19 paper)

Segmentation models with pretrained backbones. PyTorch.

Open Information Extraction (OpenIE) and Open Relation Extraction (ORE) papers and data.

Pytorch code for semantic segmentation using ERFNet

Tensorflow 2.3.0 implementation of DeepLabV3-Plus

Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

A native Tensorflow implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions (2016). Optionally uses the pretrained weights by the authors.

CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

Information Extraction System can perform NLP tasks like Named Entity Recognition, Sentence Simplification, Relation Extraction etc.

Paper notes for Information Extraction, including Relation Extraction (RE), Named Entity Recognition (NER), Entity Linking (EL), Event Extraction (EE), Named Entity Disambiguation (NED).

Graph Convolution over Pruned Dependency Trees Improves Relation Extraction (authors' PyTorch implementation)

Multiple-Relations-Extraction-Only-Look-Once. Just look at the sentence once and extract the multiple pairs of entities and their corresponding relations. 端到端联合多关系抽取模型，可用于 http://lic2019.ccf.org.cn/kg 信息抽取。

The Libre Multilingual Analyzer, a Natural Language Processing (NLP) C++ toolkit.

BERT + reproduce "Joint entity recognition and relation extraction as a multi-head selection problem" for Chinese and English IE

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

ResUNet++, CRF, and TTA for segmentation of medical images (IEEE JBIHI)

A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.

BCDU-Net : Medical Image Segmentation

Semantic Segmentation PyTorch code for our paper: Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

Training & Quantization of embedded friendly Deep Learning / Machine Learning / Computer Vision models

Summary and experiment includes basic segmentation, human segmentation, human or portrait matting for both image and video.

CNNs for semantic segmentation using Keras library

Tensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.

Tensorflow implementation : U-net and FCN with global convolution

A framework for training segmentation models in pytorch on labelme annotations with pretrained examples of skin, cat, and pizza topping segmentation

Indirect Supervision for Relation Extraction Using Question-Answer Pairs (WSDM'18)

Collection of computer vision models, ready to be included in a JVM project

An awesome semantic segmentation model that runs in real time

segmentation paper reading notes

CogIE: An Information Extraction Toolkit for Bridging Text and CogNet. ACL 2021

Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

Pretrained Span and span Pair Encoder, code for "Pre-training Entity Relation Encoder with Intra-span and Inter-spanInformation.", EMNLP2020. It is based on our NERE toolkit (https://github.com/Receiling/NERE).

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

A curated list of Open Information Extraction (OIE) resources: papers, code, data, etc.

PyTorch implementation of the position-aware attention model for relation extraction

A Novel Cascade Binary Tagging Framework for Relational Triple Extraction. Accepted by ACL 2020.

Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks

[AKBC 19] Improving Relation Extraction by Pre-trained Language Representations

[ACL 19] Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction

Chinese Named Entity Recognition with IDCNN/biLSTM+CRF, and Relation Extraction with biGRU+2ATT 中文实体识别与关系提取

Distantly Supervised Relation Extraction

Binary semantic segmentation with UNet based on MobileNetV2 encoder

FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC

Sandbox for training deep learning networks

Knowledge triples extraction and knowledge base construction based on dependency syntax for open domain text.

[MICCAI2022] This is an official PyTorch implementation for A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

The implementation of 3D-UNet using PyTorch