PyTorch_Semantic_Segmentation
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Implement some models of RGB/RGBD semantic segmentation in PyTorch, easy to run. Such as FCN, RefineNet, PSPNet, RDFNet, 3DGNN, PointNet, DeepLab V3, DeepLab V3 plus, DenseASPP, FastFCN
PyTorch_Semantic_Segmentation
Implement some models of semantic segmentation in PyTorch, easy to run.
Introduction
- This repo includes some networks for Semantic Segmentation implemented in pytorch 1.0.0 and python3. See each directory for more information.
- I only provide architecture of network here. Dataset and train/test files aren't available here, for I think it can be added according to individual needs.
- The code file containing the network structure can be run directly with the set simulation data.
- ResNet101 used in this repo is the one which PSPNet used. The difference between this resnet and the original resnet is that the first 7*7 conv layer in the old version is replaced by three small-kernel convs. Pretrained model can be downloaded from here.
Has finished
FCN8s
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RefineNet (CVPR 2017)
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PSPNet (CVPR 2017)
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PointNet (CVPR 2017)
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RDFNet (ICCV 2017)
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3DGNN (ICCV 2017)
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DeepLab V3
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DeepLab V3+ (ECCV 2018)
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DenseASPP (CVPR 2018)
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FastFCN (Arxiv 2019)
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