950 Repositories
Python sentence-segmentation Libraries
A PyTorch implementation of PointRend: Image Segmentation as Rendering
PointRend A PyTorch implementation of PointRend: Image Segmentation as Rendering [arxiv] [Official Implementation: Detectron2] This repo for Only Sema
Unet network with mean teacher for altrasound image segmentation
Unet network with mean teacher for altrasound image segmentation
Video Object Segmentation(VOS) From Zero to HeroVideo Object Segmentation(VOS) From Zero to Hero
Video Object Segmentation(VOS) From Zero to Hero! Goal 1:train a two layers cnn model for vos. Finish! see model.py FFNet for more diteal.(2021.9.30)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)
LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
Swin Transformer for Semantic Segmentation of satellite images This repo contains the supported code and configuration files to reproduce semantic seg
Continuous Conditional Random Field Convolution for Point Cloud Segmentation
CRFConv This repository is the implementation of "Continuous Conditional Random Field Convolution for Point Cloud Segmentation" 1. Setup 1) Building c
The Official PyTorch Implementation of DiscoBox.
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Paper | Project page | Demo (Youtube) | Demo (Bilib
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation Paper Multi-Target Adversarial Frameworks for Domain Adaptation in
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation (NeurIPS2021 Benchmark and Dataset Track)
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021)
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is
LIVECell - A large-scale dataset for label-free live cell segmentation
LIVECell dataset This document contains instructions of how to access the data associated with the submitted manuscript "LIVECell - A large-scale data
Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation.
Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
a basic code repository for basic task in CV(classification,detection,segmentation)
basic_cv a basic code repository for basic task in CV(classification,detection,segmentation,tracking) classification generate dataset train predict de
GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
GndNet: Fast Ground plane Estimation and Point Cloud Segmentation for Autonomous Vehicles. Authors: Anshul Paigwar, Ozgur Erkent, David Sierra Gonzale
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
The Official PyTorch Implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
Perform oocyst segmentation in mercurochrome stained mosquito midgut
Midgut_oocyst_segmentation Perform oocyst segmentation in mercurochrome stained mosquito midguts This oocyst segmentation model also powers the webtoo
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
A 3D multi-modal medical image segmentation library in PyTorch We strongly believe in open and reproducible deep learning research. Our goal is to imp
Deep Multi-Magnification Network for multi-class tissue segmentation of whole slide images
Deep Multi-Magnification Network This repository provides training and inference codes for Deep Multi-Magnification Network published here. Deep Multi
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)
Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd
Transfer-Learn is an open-source and well-documented library for Transfer Learning.
Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.
PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation (TPAMI).
PFENet This is the implementation of our paper PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation that has been accepted to IEE
Codes of paper "Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling"
Unseen Object Amodal Instance Segmentation (UOAIS) Seunghyeok Back, Joosoon Lee, Taewon Kim, Sangjun Noh, Raeyoung Kang, Seongho Bak, Kyoobin Lee This
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
PyTorch Project Template is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial PyTorch P
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
Pytorch implementation of convolutional neural network visualization techniques
Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)
Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim
End-to-end image segmentation kit based on PaddlePaddle.
English | 简体中文 PaddleSeg PaddleSeg has released the new version including the following features: Our team won the AutoNUE@CVPR 2021 challenge, where
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
Semi-supervised-learning-for-medical-image-segmentation. Recently, semi-supervised image segmentation has become a hot topic in medical image computin
Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)
Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim
An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc.
An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc.
Add filters (background blur, etc) to your webcam on Linux.
Add filters (background blur, etc) to your webcam on Linux.
CondNet: Conditional Classifier for Scene Segmentation
CondNet: Conditional Classifier for Scene Segmentation Introduction The fully convolutional network (FCN) has achieved tremendous success in dense vis
An extremely simple, intuitive, hardware-friendly, and well-performing network structure for LiDAR semantic segmentation on 2D range image. IROS21
FIDNet_SemanticKITTI Motivation Implementing complicated network modules with only one or two points improvement on hardware is tedious. So here we pr
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
An implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional Neural Network"
Retina Blood Vessels Segmentation This is an implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional
DeepLab resnet v2 model in pytorch
pytorch-deeplab-resnet DeepLab resnet v2 model implementation in pytorch. The architecture of deepLab-ResNet has been replicated exactly as it is from
CNNs for Sentence Classification in PyTorch
Introduction This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch. Kim's implementation of t
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
A PyTorch implementation of V-Net Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Imag
Pixel-wise segmentation on VOC2012 dataset using pytorch.
PiWiSe Pixel-wise segmentation on the VOC2012 dataset using pytorch. FCN SegNet PSPNet UNet RefineNet For a more complete implementation of segmentati
Applying "Load What You Need: Smaller Versions of Multilingual BERT" to LaBSE
smaller-LaBSE LaBSE(Language-agnostic BERT Sentence Embedding) is a very good method to get sentence embeddings across languages. But it is hard to fi
Segmentation for medical image.
EfficientSegmentation Introduction EfficientSegmentation is an open source, PyTorch-based segmentation framework for 3D medical image. Features A whol
[MedIA2021]MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning
MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning [MedIA or Arxiv] and [Demo] This repository pr
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig
Search Git commits in natural language
NaLCoS - NAtural Language COmmit Search Search commit messages in your repository in natural language. NaLCoS (NAtural Language COmmit Search) is a co
Line as a Visual Sentence: Context-aware Line Descriptor for Visual Localization
Line as a Visual Sentence with LineTR This repository contains the inference code, pretrained model, and demo scripts of the following paper. It suppo
Demo for the paper "Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation"
Streaming speaker diarization Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation by Juan Manuel Coria, Hervé
Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers (arXiv2021)
Polyp-PVT by Bo Dong, Wenhai Wang, Deng-Ping Fan, Jinpeng Li, Huazhu Fu, & Ling Shao. This repo is the official implementation of "Polyp-PVT: Polyp Se
Official implementation of the ICCV 2021 paper "Joint Inductive and Transductive Learning for Video Object Segmentation"
JOINT This is the official implementation of Joint Inductive and Transductive learning for Video Object Segmentation, to appear in ICCV 2021. @inproce
Demo for the paper "Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation"
Streaming speaker diarization Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation by Juan Manuel Coria, Hervé
Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019)
Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019) Introduction Official implementation of Dynamic Multi-scale Filters for Semant
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation The code of: Cross-Image Region Mining with Region Proto
This repository contains the PyTorch implementation of the paper STaCK: Sentence Ordering with Temporal Commonsense Knowledge appearing at EMNLP 2021.
STaCK: Sentence Ordering with Temporal Commonsense Knowledge This repository contains the pytorch implementation of the paper STaCK: Sentence Ordering
基于Pytorch实现优秀的自然图像分割框架!(包括FCN、U-Net和Deeplab)
语义分割学习实验-基于VOC数据集 usage: 下载VOC数据集,将JPEGImages SegmentationClass两个文件夹放入到data文件夹下。 终端切换到目标目录,运行python train.py -h查看训练 (torch) qust116-jq@qustx-X299-WU8:
🍊 PAUSE (Positive and Annealed Unlabeled Sentence Embedding), accepted by EMNLP'2021 🌴
PAUSE: Positive and Annealed Unlabeled Sentence Embedding Sentence embedding refers to a set of effective and versatile techniques for converting raw
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
Code for Boundary-Aware Segmentation Network for Mobile and Web Applications
BASNet Boundary-Aware Segmentation Network for Mobile and Web Applications This repository contain implementation of BASNet in tensorflow/keras. comme
[2021][ICCV][FSNet] Full-Duplex Strategy for Video Object Segmentation
Full-Duplex Strategy for Video Object Segmentation (ICCV, 2021) Authors: Ge-Peng Ji, Keren Fu, Zhe Wu, Deng-Ping Fan*, Jianbing Shen, & Ling Shao This
nnFormer: Interleaved Transformer for Volumetric Segmentation Code for paper "nnFormer: Interleaved Transformer for Volumetric Segmentation "
nnFormer: Interleaved Transformer for Volumetric Segmentation Code for paper "nnFormer: Interleaved Transformer for Volumetric Segmentation ". Please
ICCV2021 - Mining Contextual Information Beyond Image for Semantic Segmentation
Introduction The official repository for "Mining Contextual Information Beyond Image for Semantic Segmentation". Our full code has been merged into ss
A scalable implementation of WobblyStitcher for 3D microscopy images
WobblyStitcher Introduction A scalable implementation of WobblyStitcher Dependencies $ python -m pip install numpy scikit-image Visualization ImageJ
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019)
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network
Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite.
TFlite Ultra Fast Lane Detection Inference Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite. So
TorchIO is a Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Lite-HRNet: A Lightweight High-Resolution Network
LiteHRNet Benchmark 🔥 🔥 Based on MMsegmentation 🔥 🔥 Cityscapes FCN resize concat config mIoU last mAcc last eval last mIoU best mAcc best eval bes
OpenCVのGrabCut()を利用したセマンティックセグメンテーション向けアノテーションツール(Annotation tool using GrabCut() of OpenCV. It can be used to create datasets for semantic segmentation.)
[Japanese/English] GrabCut-Annotation-Tool GrabCut-Annotation-Tool.mp4 OpenCVのGrabCut()を利用したアノテーションツールです。 セマンティックセグメンテーション向けのデータセット作成にご使用いただけます。 ※Grab
A data annotation pipeline to generate high-quality, large-scale speech datasets with machine pre-labeling and fully manual auditing.
About This repository provides data and code for the paper: Scalable Data Annotation Pipeline for High-Quality Large Speech Datasets Development (subm
Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
Pytorch-NLU,一个中文文本分类、序列标注工具包,支持中文长文本、短文本的多类、多标签分类任务,支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
Add filters (background blur, etc) to your webcam on Linux.
webcam-filters Add filters (background blur, etc) to your webcam on Linux. Video conferencing applications tend to either lack video effects altogethe
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks
SSTNet Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks(ICCV2021) by Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui J
Semantic Segmentation with Pytorch-Lightning
This is a simple demo for performing semantic segmentation on the Kitti dataset using Pytorch-Lightning and optimizing the neural network by monitoring and comparing runs with Weights & Biases.
Deep Learning for 3D Point Clouds: A Survey (IEEE TPAMI, 2020)
🔥Deep Learning for 3D Point Clouds (IEEE TPAMI, 2020)
PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or
PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)
PrimitiveNet Source code for the paper: Jingwei Huang, Yanfeng Zhang, Mingwei Sun. [PrimitiveNet: Primitive Instance Segmentation with Local Primitive
使用OpenCV部署全景驾驶感知网络YOLOP,可同时处理交通目标检测、可驾驶区域分割、车道线检测,三项视觉感知任务,包含C++和Python两种版本的程序实现。本套程序只依赖opencv库就可以运行, 从而彻底摆脱对任何深度学习框架的依赖。
YOLOP-opencv-dnn 使用OpenCV部署全景驾驶感知网络YOLOP,可同时处理交通目标检测、可驾驶区域分割、车道线检测,三项视觉感知任务,依然是包含C++和Python两种版本的程序实现 onnx文件从百度云盘下载,链接:https://pan.baidu.com/s/1A_9cldU
sssegmentation is a general framework for our research on strongly supervised semantic segmentation.
sssegmentation is a general framework for our research on strongly supervised semantic segmentation.
Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.
Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.
Implementation for paper: Self-Regulation for Semantic Segmentation
Self-Regulation for Semantic Segmentation This is the PyTorch implementation for paper Self-Regulation for Semantic Segmentation, ICCV 2021. Citing SR
Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery (ICCV 2021)
Change is Everywhere Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery by Zhuo Zheng, Ailong Ma, Liangpei Zhang and Yanfei
TorchDistiller - a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.
This project is a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.
PyTorch implementation of PSPNet segmentation network
pspnet-pytorch PyTorch implementation of PSPNet segmentation network Original paper Pyramid Scene Parsing Network Details This is a slightly different
This is the offical website for paper ''Category-consistent deep network learning for accurate vehicle logo recognition''
The Pytorch Implementation of Category-consistent deep network learning for accurate vehicle logo recognition This is the offical website for paper ''
Jittor Medical Segmentation Lib -- The assignment of Pattern Recognition course (2021 Spring) in Tsinghua University
THU模式识别2021春 -- Jittor 医学图像分割 模型列表 本仓库收录了课程作业中同学们采用jittor框架实现的如下模型: UNet SegNet DeepLab V2 DANet EANet HarDNet及其改动HarDNet_alter PSPNet OCNet OCRNet DL
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco
ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation
ST++ This is the official PyTorch implementation of our paper: ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation. Lihe Ya
An official implementation of "Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation" (ICCV 2021) in PyTorch.
Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation This is an official implementation of the paper "Exploiting a Joint
Korean Simple Contrastive Learning of Sentence Embeddings using SKT KoBERT and kakaobrain KorNLU dataset
KoSimCSE Korean Simple Contrastive Learning of Sentence Embeddings implementation using pytorch SimCSE Installation git clone https://github.com/BM-K/
Context Axial Reverse Attention Network for Small Medical Objects Segmentation
CaraNet: Context Axial Reverse Attention Network for Small Medical Objects Segmentation This repository contains the implementation of a novel attenti
Pytorch Implementation for NeurIPS (oral) paper: Pixel Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation
Pixel-Level Cycle Association This is the Pytorch implementation of our NeurIPS 2020 Oral paper Pixel-Level Cycle Association: A New Perspective for D
This is an official implementation of the High-Resolution Transformer for Dense Prediction.
High-Resolution Transformer for Dense Prediction Introduction This is the official implementation of High-Resolution Transformer (HRT). We present a H
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation (ICCV2021)
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation This is a pytorch project for the paper Dynamic Divide-and-Conquer Ad
Action Segmentation Evaluation
Reference Action Segmentation Evaluation Code This repository contains the reference code for action segmentation evaluation. If you have a bug-fix/im
Vision-Language Transformer and Query Generation for Referring Segmentation (ICCV 2021)
Vision-Language Transformer and Query Generation for Referring Segmentation Please consider citing our paper in your publications if the project helps
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da