deeplabv3plus (Google's new algorithm for semantic segmentation) in keras:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
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Updated
Mar 25, 2018 - Python
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
A Tensorflow implementation of Deeplabv3+ trained on VOC2012.
DeepLabV3Plus for Beginners in Cityscapes Dataset
LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)
In search of effective and efficient Pipeline for Distillating Knowledge in Convolutional Neural Networks
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).
minimal-segmentation
Monocular Depth Estimation via a Fully Convolutional Deep Neural Network, utilising Atrous Convolutions, with 3D Point Cloud Visualisation.
Human segmentation project(pytorch)
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.
Use DeeplabV3+ to segment the flexor tendon, median nerve, and carpal tunnel separately from MR images.
A semantic segmentation toolbox based on PyTorch
In this program, we are using image segmentation to remove the background from photos.
Tensorflow-Keras semantic segmentation
Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes
DeepLabv3+ built in TensorFlow
I am aiming to write different Semantic Segmentation models from scratch with different pretrained backbones.
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