2059 Repositories
Python chinese-text-segmentation Libraries
Text to image synthesis using thought vectors
Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
StackGAN Pytorch implementation Inception score evaluation StackGAN-v2-pytorch Tensorflow implementation for reproducing main results in the paper Sta
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
Learning Chinese Character style with conditional GAN
zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(字到字, me
A Python3 script that simulates the user typing a text on their keyboard.
A Python3 script that simulates the user typing a text on their keyboard. (control the speed, randomness, rate of typos and more!)
Napari plugin for iteratively improving 3D instance segmentation of cells (u-net x watershed)
iterseg napari plugin for iteratively improving unet-watershed segmentation This napari plugin was generated with Cookiecutter using @napari's cookiec
A Simple and Versatile Framework for Object Detection and Instance Recognition
SimpleDet - A Simple and Versatile Framework for Object Detection and Instance Recognition Major Features FP16 training for memory saving and up to 2.
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
Buckshot++ is a new algorithm that finds highly stable clusters efficiently.
Buckshot++: An Outlier-Resistant and Scalable Clustering Algorithm. (Inspired by the Buckshot Algorithm.) Here, we introduce a new algorithm, which we
Convert a DOS Punk image to text
DOS Punk Text Inspired by MAX CAPACITY's DOS Punks & the amazing DOS Punk community. DOS Punk Text is a Python 3 script that renders a DOS Punk image
Self-supervised Multi-modal Hybrid Fusion Network for Brain Tumor Segmentation
JBHI-Pytorch This repository contains a reference implementation of the algorithms described in our paper "Self-supervised Multi-modal Hybrid Fusion N
A socket script to obtain chinese phones-sequence for any english word
Foreign Pronunciation Generator (English-Chinese) We provide a simple socket script for acquiring Chinese pronunciation of English words (phones in ai
A collection of pre-commit hooks for handling text files.
texthooks A collection of pre-commit hooks for handling text files. In particular, hooks for handling unicode characters which may be undesirable in a
A deep-learning pipeline for segmentation of ambiguous microscopic images.
Welcome to Official repository of deepflash2 - a deep-learning pipeline for segmentation of ambiguous microscopic images. Quick Start in 30 seconds se
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar
Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
DeepXML Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents Architectures and algorithms DeepXML supports
This repository is maintained for the scientific paper tittled " Study of keyword extraction techniques for Electric Double Layer Capacitor domain using text similarity indexes: An experimental analysis "
kwd-extraction-study This repository is maintained for the scientific paper tittled " Study of keyword extraction techniques for Electric Double Layer
[CVPRW 2021] - Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation
ObjProp Introduction This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Insta
D²Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos
D²Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos This repository contains the implementation for "D²Conv3D: Dynamic Dilated Co
Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition
Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition | paper | dataset | pretrained detection model | Authors: Yi-Chang Che
Code-free deep segmentation for computational pathology
NoCodeSeg: Deep segmentation made easy! This is the official repository for the manuscript "Code-free development and deployment of deep segmentation
DataCLUE: 国内首个以数据为中心的AI测评(含模型分析报告)
DataCLUE: A Benchmark Suite for Data-centric NLP You can get the english version of README. 以数据为中心的AI测评(DataCLUE) 内容导引 章节 描述 简介 介绍以数据为中心的AI测评(DataCLUE
Official implementation of Meta-StyleSpeech and StyleSpeech
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code
Text-to-Music Retrieval using Pre-defined/Data-driven Emotion Embeddings
Text2Music Emotion Embedding Text-to-Music Retrieval using Pre-defined/Data-driven Emotion Embeddings Reference Emotion Embedding Spaces for Matching
Code repo for "FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation" (ICCV 2021)
FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation (ICCV 2021) This repository contains the implementation of th
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig
A Sublime Text package that allows a user to view all the available core/plugin commands for Sublime Text and Sublime Merge, along with their documentation/source.
CommandsBrowser A Sublime Text package that allows a user to view all the available core/plugin commands for Sublime Text and Sublime Merge, along wit
This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation".
[CVPRW 2021] - Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation
A relatively simple python program to generate one of those reddit text to speech videos dominating youtube.
Reddit text to speech generator A basic reddit tts video generator Current functionality Generate videos for subs based on comments,(askreddit) so rea
Gated-Shape CNN for Semantic Segmentation (ICCV 2019)
GSCNN This is the official code for: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation Towaki Takikawa, David Acuna, Varun Jampani, Sanja Fidler
Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device" @ CAD&Graphics2019
PortraitNet Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device". @ CAD&Graphics 2019 Introduction We propose a
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation.
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation [Project] [Paper] [arXiv] [Home] Official implementation of FastFCN:
PyTorch implementation of UNet++ (Nested U-Net).
PyTorch implementation of UNet++ (Nested U-Net) This repository contains code for a image segmentation model based on UNet++: A Nested U-Net Architect
Extreme Lightwegith Portrait Segmentation
Extreme Lightwegith Portrait Segmentation Please go to this link to download code Requirements python 3 pytorch = 0.4.1 torchvision==0.2.1 opencv-pyt
reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
DFANet This repo is an unofficial pytorch implementation of DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation log 2019.4.16 After 48
Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image
This repository contains the reference implementation for our proposed Convolutional CRFs.
ConvCRF This repository contains the reference implementation for our proposed Convolutional CRFs in PyTorch (Tensorflow planned). The two main entry-
UPSNet: A Unified Panoptic Segmentation Network
UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te
High-resolution networks and Segmentation Transformer for Semantic Segmentation
High-resolution networks and Segmentation Transformer for Semantic Segmentation Branches This is the implementation for HRNet + OCR. The PyTroch 1.1 v
Unofficial implementation of Fast-SCNN: Fast Semantic Segmentation Network
Fast-SCNN: Fast Semantic Segmentation Network Unofficial implementation of the model architecture of Fast-SCNN. Real-time Semantic Segmentation and mo
CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).
CCNet: Criss-Cross Attention for Semantic Segmentation Paper Links: Our most recent TPAMI version with improvements and extensions (Earlier ICCV versi
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation This repository contains the source code of our paper, ESPNet (acc
Using modified BiSeNet for face parsing in PyTorch
face-parsing.PyTorch Contents Training Demo References Training Prepare training data: -- download CelebAMask-HQ dataset -- change file path in the pr
Fast, modular reference implementation and easy training of Semantic Segmentation algorithms in PyTorch.
TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De
Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation
Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation This implementation is based on orobix implement
implementation for paper "ShelfNet for fast semantic segmentation"
ShelfNet-lightweight for paper (ShelfNet for fast semantic segmentation) This repo contains implementation of ShelfNet-lightweight models for real-tim
Dual Attention Network for Scene Segmentation (CVPR2019)
Dual Attention Network for Scene Segmentation(CVPR2019) Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang,and Hanqing Lu Introduction W
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor
Understanding Convolution for Semantic Segmentation
TuSimple-DUC by Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell. Introduction This repository is for Under
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s
RTSeg: Real-time Semantic Segmentation Comparative Study
Real-time Semantic Segmentation Comparative Study The repository contains the official TensorFlow code used in our papers: RTSEG: REAL-TIME SEMANTIC S
Tensorflow Implementation of Pixel Transposed Convolutional Networks (PixelTCN and PixelTCL)
Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel
Chainer Implementation of Semantic Segmentation using Adversarial Networks
Semantic Segmentation using Adversarial Networks Requirements Chainer (1.23.0) Differences Use of FCN-VGG16 instead of Dilated8 as Segmentor. Caution
Segmentation-Aware Convolutional Networks Using Local Attention Masks
Segmentation-Aware Convolutional Networks Using Local Attention Masks [Project Page] [Paper] Segmentation-aware convolution filters are invariant to b
A Kitti Road Segmentation model implemented in tensorflow.
KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark
code and models for "Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation"
Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation This repository contains code and models for the method described in: Golnaz
Full Resolution Residual Networks for Semantic Image Segmentation
Full-Resolution Residual Networks (FRRN) This repository contains code to train and qualitatively evaluate Full-Resolution Residual Networks (FRRNs) a
Tensorflow implementation of "Learning Deconvolution Network for Semantic Segmentation"
Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation. Install Instructions Works with tensorflow 1.11.0 and uses the
DeconvNet : Learning Deconvolution Network for Semantic Segmentation
DeconvNet: Learning Deconvolution Network for Semantic Segmentation Created by Hyeonwoo Noh, Seunghoon Hong and Bohyung Han at POSTECH Acknowledgement
PyTorch implementation of PSPNet
PSPNet with PyTorch Unofficial implementation of "Pyramid Scene Parsing Network" (https://arxiv.org/abs/1612.01105). This repository is just for caffe
TensorFlow-based implementation of "Pyramid Scene Parsing Network".
PSPNet_tensorflow Important Code is fine for inference. However, the training code is just for reference and might be only used for fine-tuning. If yo
PSPNet in Chainer
PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for
Pytorch code for semantic segmentation using ERFNet
ERFNet (PyTorch version) This code is a toolbox that uses PyTorch for training and evaluating the ERFNet architecture for semantic segmentation. For t
This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation.
ERFNet This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation. NEW!! New PyTorch
ICNet and PSPNet-50 in Tensorflow for real-time semantic segmentation
Real-Time Semantic Segmentation in TensorFlow Perform pixel-wise semantic segmentation on high-resolution images in real-time with Image Cascade Netwo
TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".
ICNet_tensorflow This repo provides a TensorFlow-based implementation of paper "ICNet for Real-Time Semantic Segmentation on High-Resolution Images,"
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K
ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018
ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a
The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at http://www.cs.cmu.edu/~aayushb/pixelNet/.
PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f
Dilated Convolution for Semantic Image Segmentation
Multi-Scale Context Aggregation by Dilated Convolutions Introduction Properties of dilated convolution are discussed in our ICLR 2016 conference paper
DilatedNet in Keras for image segmentation
Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A
Keras Implementation of The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation by (Simon Jégou, Michal Drozdzal, David Vazquez, Adriana Romero, Yoshua Bengio)
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation: Work In Progress, Results can't be replicated yet with the m
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th
Fully Convolutional DenseNets for semantic segmentation.
Introduction This repo contains the code to train and evaluate FC-DenseNets as described in The One Hundred Layers Tiramisu: Fully Convolutional Dense
TensorFlow implementation of ENet
TensorFlow-ENet TensorFlow implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. This model was tested on th
TensorFlow implementation of ENet, trained on the Cityscapes dataset.
segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation.
ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN
A TensorFlow implementation of FCN-8s
FCN-8s implementation in TensorFlow Contents Overview Examples and demo video Dependencies How to use it Download pre-trained VGG-16 Overview This is
Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.
semantic-segmentation-tensorflow This is a Tensorflow implementation of semantic segmentation models on MIT ADE20K scene parsing dataset and Cityscape
Using fully convolutional networks for semantic segmentation with caffe for the cityscapes dataset
Using fully convolutional networks for semantic segmentation (Shelhamer et al.) with caffe for the cityscapes dataset How to get started Download the
Segmentation vgg16 fcn - cityscapes
VGGSegmentation Segmentation vgg16 fcn - cityscapes Priprema skupa skripta prepare_dataset_downsampled.py Iz slika cityscapesa izrezuje haubu automobi
Fully convolutional networks for semantic segmentation
FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo
Pytorch for Segmentation
Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to
Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as
A tensorflow implementation of Fully Convolutional Networks For Semantic Segmentation
##A tensorflow implementation of Fully Convolutional Networks For Semantic Segmentation. #USAGE To run the trained classifier on some images: python w
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation
FCN.tensorflow Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (FCNs). The implementation is largely based on the
FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation
FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This
Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation(Unfinished)
Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas
An Implementation of Fully Convolutional Networks in Tensorflow.
Update An example on how to integrate this code into your own semantic segmentation pipeline can be found in my KittiSeg project repository. tensorflo
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
Fully Convolutional Networks for Semantic Segmentation This is the reference implementation of the models and code for the fully convolutional network
A MatConvNet-based implementation of the Fully-Convolutional Networks for image segmentation
MatConvNet implementation of the FCN models for semantic segmentation This package contains an implementation of the FCN models (training and evaluati
PyTorch implementation of DeepLab v2 on COCO-Stuff / PASCAL VOC
DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC
PyTorch Implementations for DeeplabV3 and PSPNet
Pytorch-segmentation-toolbox DOC Pytorch code for semantic segmentation. This is a minimal code to run PSPnet and Deeplabv3 on Cityscape dataset. Shor
Train DeepLab for Semantic Image Segmentation
Train DeepLab for Semantic Image Segmentation Martin Kersner, [email protected] This repository contains scripts for training DeepLab for Semantic I
This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset.
DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Up
DeepLab-ResNet rebuilt in TensorFlow
DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Fr
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.
DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute
SegNet including indices pooling for Semantic Segmentation with tensorflow and keras
SegNet SegNet is a model of semantic segmentation based on Fully Comvolutional Network. This repository contains the implementation of learning and te