Deeplabv3plus Collection

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🔮Psychic

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“Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes”

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“DeepLabv3+ built in TensorFlow ”

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

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“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) ”

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🔥Fire

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“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.”

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🔮Psychic

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“A semantic segmentation toolbox based on PyTorch”

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“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).”

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📦Normal

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“Tensorflow 2.3.0 implementation of DeepLabV3-Plus”

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📦Normal

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“Clothing segmentation with DeepLabV3+”

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“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.”

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

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🔮Psychic

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“All version of deeplab implemented in Pytorch”