Tramac / awesome-semantic-segmentation-pytorch

Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
Apache License 2.0
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DenseASPP与官方代码似乎实现的不太一样(different implemantation with official code in DenseASPP) #200

Open PoloWitty opened 2 years ago

PoloWitty commented 2 years ago

When I try to reimplement the DenseASPP, I refer to both the official code and this repo, but when it comes to DenseASPP head, I notice the order of conv and norm in DenseASPP block is different.

In official code, it's norm->relu->conv->norm->relu->conv, in this repo, it's conv->norm->relu->conv->norm->relu.

Just the preact form of conv and postact form of convolution, is that mean the postact form performs better in semantic segmentation after your experiment?