Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes

DeepLabv3+ built in TensorFlow

Support PointRend, Fast_SCNN, HRNet, Deeplabv3_plus(xception, resnet, mobilenet), ContextNet, FPENet, DABNet, EdaNet, ENet, Espnetv2, RefineNet, UNet, DANet, HRNet, DFANet, HardNet, LedNet, OCNet, EncNet, DuNet, CGNet, CCNet, BiSeNet, PSPNet, ICNet, FCN, deeplab)

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

A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.

A semantic segmentation toolbox based on PyTorch

mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).

Tensorflow 2.3.0 implementation of DeepLabV3-Plus

Clothing segmentation with DeepLabV3+

The remote sensing image semantic segmentation repository based on tf.keras includes backbone networks such as resnet, densenet, mobilenet, and segmentation networks such as deeplabv3+, pspnet, panet, and refinenet.

deeplabv3plus (Google's new algorithm for semantic segmentation) in keras：Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

All version of deeplab implemented in Pytorch

No description provided.

In this program, we are using image segmentation to remove the background from photos.

Human segmentation project(pytorch)

The deeplabv3+ person segmentation android example.

The inference implementation of the deeplabV3+ person segementation algorithm.

A Tensorflow implementation of Deep Lab V3 Plus from scratch.

DeepLabV3Plus for Beginners in Cityscapes Dataset

PyTorch Implementation of Semantic Segmentation CNNs: This repository features key architectures like UNet, DeepLabv3+, SegNet, FCN, and PSPNet. It's crafted to provide a solid foundation for Semantic Segmentation tasks using PyTorch.

Tensorflow-Keras semantic segmentation

In search of effective and efficient Pipeline for Distillating Knowledge in Convolutional Neural Networks

Monocular Depth Estimation via a Fully Convolutional Deep Neural Network, utilising Atrous Convolutions, with 3D Point Cloud Visualisation.

Source code for "Amodal Instance Segmentation and Multi-Object Tracking with Deep Pixel Embedding"

This repo hosts the water body extraction from satellite images using DeeplabV3+ model.

A Tensorflow implementation of Deeplabv3+ trained on VOC2012.

I am aiming to write different Semantic Segmentation models from scratch with different pretrained backbones.

百度车道线比赛

Fine-tune and evaluate deep learning models built with PyTorch for semantic segmentation of trees from satellite imagery of forestry areas.

Image segmentation using deeplab