Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes

DeepLabv3+ built in TensorFlow

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

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)

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.

SimpleAICV:pytorch training and testing examples.

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

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

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.

All version of deeplab implemented in Pytorch

Clothing segmentation with DeepLabV3+

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