1366 Repositories
Python weakly-supervised-segmentation Libraries
A library for Multilingual Unsupervised or Supervised word Embeddings
MUSE: Multilingual Unsupervised and Supervised Embeddings MUSE is a Python library for multilingual word embeddings, whose goal is to provide the comm
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
Transparent Transformer Segmentation
Transparent Transformer Segmentation Introduction This repository contains the data and code for IJCAI 2021 paper Segmenting transparent object in the
Source codes for the paper "Local Additivity Based Data Augmentation for Semi-supervised NER"
LADA This repo contains codes for the following paper: Jiaao Chen*, Zhenghui Wang*, Ran Tian, Zichao Yang, Diyi Yang: Local Additivity Based Data Augm
Learning Representational Invariances for Data-Efficient Action Recognition
Learning Representational Invariances for Data-Efficient Action Recognition Official PyTorch implementation for Learning Representational Invariances
(IEEE TIP 2021) Regularized Densely-connected Pyramid Network for Salient Instance Segmentation
RDPNet IEEE TIP 2021: Regularized Densely-connected Pyramid Network for Salient Instance Segmentation PyTorch training and testing code are available.
ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)
This is the project page for the paper: ISTR: End-to-End Instance Segmentation via Transformers, Jie Hu, Liujuan Cao, Yao Lu, ShengChuan Zhang, Yan Wa
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation (CVPR 2021)
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Input Image Initial CAM Successive Maps with adversar
Pytorch implementation of CoCon: A Self-Supervised Approach for Controlled Text Generation
COCON_ICLR2021 This is our Pytorch implementation of COCON. CoCon: A Self-Supervised Approach for Controlled Text Generation (ICLR 2021) Alvin Chan, Y
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
Self-Supervised Vision Transformers with DINO PyTorch implementation and pretrained models for DINO. For details, see Emerging Properties in Self-Supe
One Stop Anomaly Shop: Anomaly detection using two-phase approach: (a) pre-labeling using statistics, Natural Language Processing and static rules; (b) anomaly scoring using supervised and unsupervised machine learning.
One Stop Anomaly Shop (OSAS) Quick start guide Step 1: Get/build the docker image Option 1: Use precompiled image (might not reflect latest changes):
Location-Sensitive Visual Recognition with Cross-IOU Loss
The trained models are temporarily unavailable, but you can train the code using reasonable computational resource. Location-Sensitive Visual Recognit
Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation
Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation (AAAI 2021) Official pytorch implementation of our paper: Discriminative
Implementation of "Efficient Regional Memory Network for Video Object Segmentation" (Xie et al., CVPR 2021).
RMNet This repository contains the source code for the paper Efficient Regional Memory Network for Video Object Segmentation. Cite this work @inprocee
[CVPR 2021] MiVOS - Mask Propagation module. Reproduced STM (and better) with training code :star2:. Semi-supervised video object segmentation evaluation.
MiVOS (CVPR 2021) - Mask Propagation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] [Papers with Code] This repo impleme
TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.
TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost
[CVPR 2021] MiVOS - Scribble to Mask module
MiVOS (CVPR 2021) - Scribble To Mask Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] A simplistic network that turns scri
SNE-RoadSeg in PyTorch, ECCV 2020
SNE-RoadSeg Introduction This is the official PyTorch implementation of SNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentati
Semi-supervised Video Deraining with Dynamical Rain Generator (CVPR, 2021, Pytorch)
S2VD Semi-supervised Video Deraining with Dynamical Rain Generator (CVPR, 2021) Requirements and Dependencies Ubuntu 16.04, cuda 10.0 Python 3.6.10, P
PyTorch code for the paper "FIERY: Future Instance Segmentation in Bird's-Eye view from Surround Monocular Cameras"
FIERY This is the PyTorch implementation for inference and training of the future prediction bird's-eye view network as described in: FIERY: Future In
BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation
BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation This is a demo implementation of BYOL for Audio (BYOL-A), a self-sup
Pytorch Implementation of LNSNet for Superpixel Segmentation
LNSNet Overview Official implementation of Learning the Superpixel in a Non-iterative and Lifelong Manner (CVPR'21) Learning Strategy The proposed LNS
Pixel Consensus Voting for Panoptic Segmentation (CVPR 2020)
Implementation for Pixel Consensus Voting (CVPR 2020). This codebase contains the essential ingredients of PCV, including various spatial discretizati
Just Go with the Flow: Self-Supervised Scene Flow Estimation
Just Go with the Flow: Self-Supervised Scene Flow Estimation Code release for the paper Just Go with the Flow: Self-Supervised Scene Flow Estimation,
SiT: Self-supervised vIsion Transformer
This repository contains the official PyTorch self-supervised pretraining, finetuning, and evaluation codes for SiT (Self-supervised image Transformer).
Training code of Spatial Time Memory Network. Semi-supervised video object segmentation.
Training-code-of-STM This repository fully reproduces Space-Time Memory Networks Performance on Davis17 val set&Weights backbone training stage traini
Object detection and instance segmentation toolkit based on PaddlePaddle.
Object detection and instance segmentation toolkit based on PaddlePaddle.
Rethinking the U-Net architecture for multimodal biomedical image segmentation
MultiResUNet Rethinking the U-Net architecture for multimodal biomedical image segmentation This repository contains the original implementation of "M
[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation
Few-shot 3D Point Cloud Semantic Segmentation Created by Na Zhao from National University of Singapore Introduction This repository contains the PyTor
Self-Supervised Learning for Domain Adaptation on Point-Clouds
Self-Supervised Learning for Domain Adaptation on Point-Clouds Introduction Self-supervised learning (SSL) allows to learn useful representations from
RefineMask (CVPR 2021)
RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features (CVPR 2021) This repo is the official implementation of RefineMask:
This is a repository for a semantic segmentation inference API using the OpenVINO toolkit
BMW-IntelOpenVINO-Segmentation-Inference-API This is a repository for a semantic segmentation inference API using the OpenVINO toolkit. It's supported
HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation Official PyTorch Implementation
: We present a novel, real-time, semantic segmentation network in which the encoder both encodes and generates the parameters (weights) of the decoder. Furthermore, to allow maximal adaptivity, the weights at each decoder block vary spatially. For this purpose, we design a new type of hypernetwork, composed of a nested U-Net for drawing higher level context features
Weakly supervised medical named entity classification
Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Introduction English | 简体中文 MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the correspondi
This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
BMW-Anonymization-Api Data privacy and individuals’ anonymity are and always have been a major concern for data-driven companies. Therefore, we design
This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit
BMW Semantic Segmentation GPU/CPU Inference API This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit. The train
Diffgram - Supervised Learning Data Platform
Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning
Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation
Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation The code of: Context Decoupling Augmentation for Weakly Supervised Semanti
PixelPick This is an official implementation of the paper "All you need are a few pixels: semantic segmentation with PixelPick."
PixelPick This is an official implementation of the paper "All you need are a few pixels: semantic segmentation with PixelPick." [Project page] [Paper
Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation
PLOP: Learning without Forgetting for Continual Semantic Segmentation This repository contains all of our code. It is a modified version of Cermelli e
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Documentation: https://mmsegmentation.readthedocs.io/ English | 简体中文 Introduction MMSegmentation is an open source semantic segmentation toolbox based
A semantic segmentation toolbox based on PyTorch
Introduction vedaseg is an open source semantic segmentation toolbox based on PyTorch. Features Modular Design We decompose the semantic segmentation
Sandbox for training deep learning networks
Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
Faster R-CNN and Mask R-CNN in PyTorch 1.0 maskrcnn-benchmark has been deprecated. Please see detectron2, which includes implementations for all model
Detectorch - detectron for PyTorch
Detectorch - detectron for PyTorch (Disclaimer: this is work in progress and does not feature all the functionalities of detectron. Currently only inf
PyTorch for Semantic Segmentation
PyTorch for Semantic Segmentation This repository contains some models for semantic segmentation and the pipeline of training and testing models, impl
The implementation of "Bootstrapping Semantic Segmentation with Regional Contrast".
ReCo - Regional Contrast This repository contains the source code of ReCo and baselines from the paper, Bootstrapping Semantic Segmentation with Regio
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement (CVPR'2020)
Under-exposure introduces a series of visual degradation, i.e. decreased visibility, intensive noise, and biased color, etc. To address these problems, we propose a novel semi-supervised learning approach for low-light image enhancement.
Implementation of DropLoss for Long-Tail Instance Segmentation in Pytorch
[AAAI 2021]DropLoss for Long-Tail Instance Segmentation [AAAI 2021] DropLoss for Long-Tail Instance Segmentation Ting-I Hsieh*, Esther Robb*, Hwann-Tz
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
Swin Transformer for Object Detection This repo contains the supported code and configuration files to reproduce object detection results of Swin Tran
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li
Official PyTorch Implementation of Hypercorrelation Squeeze for Few-Shot Segmentation, arXiv 2021
Hypercorrelation Squeeze for Few-Shot Segmentation This is the implementation of the paper "Hypercorrelation Squeeze for Few-Shot Segmentation" by Juh
Use unsupervised and supervised learning to predict stocks
AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.
InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea
Official code for the CVPR 2021 paper "How Well Do Self-Supervised Models Transfer?"
How Well Do Self-Supervised Models Transfer? This repository hosts the code for the experiments in the CVPR 2021 paper How Well Do Self-Supervised Mod
Semi-supervised Learning for Sentiment Analysis
Neural-Semi-supervised-Learning-for-Text-Classification-Under-Large-Scale-Pretraining Code, models and Datasets for《Neural Semi-supervised Learning fo
Block-wisely Supervised Neural Architecture Search with Knowledge Distillation (CVPR 2020)
DNA This repository provides the code of our paper: Blockwisely Supervised Neural Architecture Search with Knowledge Distillation. Illustration of DNA
SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021]
SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021] Pdf: https://openreview.net/forum?id=v5gjXpmR8J Code for our ICLR 2021 pape
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
A collection of loss functions for medical image segmentation
A collection of loss functions for medical image segmentation
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains (IJCV submission)
wsss-analysis The code of: A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains, arXiv pre-print 2019 paper.
UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning
UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning This is the official PyTorch implementation for UniMoCo pape
Code for CVPR 2021 paper: Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning
Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning This is the PyTorch companion code for the paper: A
Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images
SASSnet Code for paper: Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images(MICCAI 2020) Our code is origin from UA-MT You can fin
git《USD-Seg:Learning Universal Shape Dictionary for Realtime Instance Segmentation》(2020) GitHub: [fig2]
USD-Seg This project is an implement of paper USD-Seg:Learning Universal Shape Dictionary for Realtime Instance Segmentation, based on FCOS detector f
Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation
Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation This paper has been accepted and early accessed
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [BCNet, CVPR 2021] This is the official pytorch implementation of BCNet built on
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021)
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021, official Pytorch implementatio
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc
High-level batteries-included neural network training library for Pytorch
Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st
PyTorch extensions for fast R&D prototyping and Kaggle farming
Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
News March 3: v0.9.97 has various bug fixes and improvements: Bug fixes for NTXentLoss Efficiency improvement for AccuracyCalculator, by using torch i
Rembg Video Virtual Green Screen Edition
Rembg Virtual Greenscreen Edition is a tool to create a green screen matte for videos
A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile
matrixprofile-ts matrixprofile-ts is a Python 2 and 3 library for evaluating time series data using the Matrix Profile algorithms developed by the Keo
STUMPY is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks
STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim
Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research) This is a PyTorch implementation of the CoMatch paper [B
PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
Contrast to Divide: self-supervised pre-training for learning with noisy labels This is an official implementation of "Contrast to Divide: self-superv
The open source code of SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation.
SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation(ICPR 2020) Overview This code is for the paper: Spatial Attention U-Net for Retinal V
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search
BossNAS This repository contains PyTorch evaluation code, retraining code and pretrained models of our paper: BossNAS: Exploring Hybrid CNN-transforme
Repository providing a wide range of self-supervised pretrained models for computer vision tasks.
Hierarchical Pretraining: Research Repository This is a research repository for reproducing the results from the project "Self-supervised pretraining
[CVPR2021 Oral] FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation.
FFB6D This is the official source code for the CVPR2021 Oral work, FFB6D: A Full Flow Biderectional Fusion Network for 6D Pose Estimation. (Arxiv) Tab
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space
FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space by Quande Liu, Cheng Chen, Ji
A collection of resources (including the papers and datasets) of OCR (Optical Character Recognition).
OCR Resources This repository contains a collection of resources (including the papers and datasets) of OCR (Optical Character Recognition). Contents
OCR system for Arabic language that converts images of typed text to machine-encoded text.
Arabic OCR OCR system for Arabic language that converts images of typed text to machine-encoded text. The system currently supports only letters (29 l
Implementation of our paper 'PixelLink: Detecting Scene Text via Instance Segmentation' in AAAI2018
Code for the AAAI18 paper PixelLink: Detecting Scene Text via Instance Segmentation, by Dan Deng, Haifeng Liu, Xuelong Li, and Deng Cai. Contributions
Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation
This is the official implementation of "Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation". For more details, please
Code for the paper STN-OCR: A single Neural Network for Text Detection and Text Recognition
STN-OCR: A single Neural Network for Text Detection and Text Recognition This repository contains the code for the paper: STN-OCR: A single Neural Net
Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"
SEE: Towards Semi-Supervised End-to-End Scene Text Recognition Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text
Repository for Scene Text Detection with Supervised Pyramid Context Network with tensorflow.
Scene-Text-Detection-with-SPCNET Unofficial repository for [Scene Text Detection with Supervised Pyramid Context Network][https://arxiv.org/abs/1811.0
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
Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.
Handwritten Line Text Recognition using Deep Learning with Tensorflow Description Use Convolutional Recurrent Neural Network to recognize the Handwrit
Handwritten Number Recognition using CNN and Character Segmentation
Handwritten-Number-Recognition-With-Image-Segmentation Info About this repository This Repository is aimed at reading handwritten images of numbers an
Document Layout Analysis
Eynollah Document Layout Analysis Introduction This tool performs document layout analysis (segmentation) from image data and returns the results as P
OCR-D-compliant page segmentation
ocrd_segment This repository aims to provide a number of OCR-D-compliant processors for layout analysis and evaluation. Installation In your virtual e
a deep learning model for page layout analysis / segmentation.
OCR Segmentation a deep learning model for page layout analysis / segmentation. dependencies tensorflow1.8 python3 dataset: uw3-framed-lines-degraded-
ocroseg - This is a deep learning model for page layout analysis / segmentation.
ocroseg This is a deep learning model for page layout analysis / segmentation. There are many different ways in which you can train and run it, but by
Page to PAGE Layout Analysis Tool
P2PaLA Page to PAGE Layout Analysis (P2PaLA) is a toolkit for Document Layout Analysis based on Neural Networks. 💥 Try our new DEMO for online baseli
Generic framework for historical document processing
dhSegment dhSegment is a tool for Historical Document Processing. Its generic approach allows to segment regions and extract content from different ty