Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes
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Updated
Nov 15, 2022 - Python
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.
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).
In this program, we are using image segmentation to remove the background from photos.
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.
Human segmentation project(pytorch)
All version of deeplab implemented in Pytorch
Clothing segmentation with DeepLabV3+
The inference implementation of the deeplabV3+ person segementation algorithm.
A Tensorflow implementation of Deep Lab V3 Plus from scratch.
Source code for "Amodal Instance Segmentation and Multi-Object Tracking with Deep Pixel Embedding"
In search of effective and efficient Pipeline for Distillating Knowledge in Convolutional Neural Networks
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