7011 Open source projects that are alternatives of or similar to Deeplabv3 Plus

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

Pytorch code for semantic segmentation using ERFNet

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

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

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

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.)

TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".

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.

An awesome semantic segmentation model that runs in real time

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HyperSeg - Official PyTorch Implementation

AttaNet for real-time semantic segmentation.

A PyTorch Implementation of Fast-SCNN: Fast Semantic Segmentation Network(PyTorch >= 1.4)

Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.

ShanghaiTech PLUS Lab Segmentation Toolbox and Benchmark

EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

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

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

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

Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

Implementation details for EDANet

SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation (ECCV2020)

Segmentation models with pretrained backbones. PyTorch.

TensorFlow-based implementation of "Pyramid Scene Parsing Network".

Code for https://arxiv.org/abs/1611.10080

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Official PyTorch implementation of SegFormer

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SOTA Semantic Segmentation Models in PyTorch

Machine Learning Project to identify an ID Card on an image

[CVPR 2021] Forecasting the panoptic segmentation of future video frames

A PyTorch implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions by Yu and Koltun.

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segmentation paper reading notes

FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC

Implementation of our paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"

Binary semantic segmentation with UNet based on MobileNetV2 encoder

FC-DenseNet in PyTorch for Semantic Segmentation

unet for image segmentation

[CVPR2020] f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation https://arxiv.org/abs/2001.10331

STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)

This repository contains the source code of our work on designing efficient CNNs for computer vision

An out-of-box human parsing representation extractor.

This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)

BCDU-Net : Medical Image Segmentation

FSGAN - Official PyTorch Implementation

VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition (ICCV 2017)

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation

[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

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3D U-Net model for volumetric semantic segmentation written in pytorch

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.

Code and dataset for the IJCAI 2021 paper "Document-level Relation Extraction as Semantic Segmentation".

IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm