Semantic segmentation models with 500 pretrained convolutional and transformer-based backbones.

DeepLab v3 model in PyTorch. Support different backbones.

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)

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

PyTorch implementation for semantic segmentation (DeepLabV3 , UNet, etc.)

LightNet : Boosted Light-weighted Networks for Real-time Semantic Segmentation

DeepGlobe Land Cover Classification Challenge遥感影像语义分割

DeepLabV3 implemented in TensorFlow2.0

semantic segmentation pytorch 语义分割

Real-time semantic image segmentation on mobile devices

Pytorch implementation and extension of "DocUnet: Document Image Unwarping via A Stacked U-Net"

图像分割算法deeplab_v3 ，基于tensorflow，中文注释，摄像头可用

This is an ongoing re-implementation of DeepLab_v3_plus on pytorch which is trained on VOC2012 and use ResNet101 for backbone.

TransDeepLab: Convolution-Free Transformer-based DeepLab v3 for Medical Image Segmentation

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

Using deepLabv3 to segment humans

DeepLabV3 with squeeze and excitation network for human image segmentation in TensorFlow 2.5.0

Try to implement deeplab v3 on pytorch according to offical demo.

Attention Deeplabv3 : Multi-level Context Attention Mechanism for Skin Lesion Segmentation

3クラス(肌、服、髪)のセマンティックセグメンテーションを実施するモデル(A model that performs semantic segmentation of 3 classes(skin, clothes, hair))