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PaddleSeg provides 45+ semantic segmentation models, 150+ well-trained models, 10+ backbones.
In PaddleSeg/configs
, we provide the config files and readme.md for all models on common dataset, e.g., PP-LiteSeg.
Besides, the readme.md file introduces the origin paper, the performance and the trained weights.
Some common models are as follows.
CNN Series
Model\Backbone Network | ResNet50 | ResNet101 | HRNetw18 | HRNetw48 |
---|---|---|---|---|
ANN | ✔ | ✔ | ||
BiSeNetv2 | - | - | - | - |
DANet | ✔ | ✔ | ||
Deeplabv3 | ✔ | ✔ | ||
Deeplabv3P | ✔ | ✔ | ||
Fast-SCNN | - | - | - | - |
FCN | ✔ | ✔ | ||
GCNet | ✔ | ✔ | ||
GSCNN | ✔ | ✔ | ||
HarDNet | - | - | - | - |
OCRNet | ✔ | ✔ | ||
PSPNet | ✔ | ✔ | ||
U-Net | - | - | - | - |
U2-Net | - | - | - | - |
Att U-Net | - | - | - | - |
U-Net++ | - | - | - | - |
U-Net3+ | - | - | - | - |
DecoupledSegNet | ✔ | ✔ | ||
EMANet | ✔ | ✔ | - | - |
ISANet | ✔ | ✔ | - | - |
DNLNet | ✔ | ✔ | - | - |
SFNet | ✔ | - | - | - |
PP-HumanSeg-Lite | - | - | - | - |
PortraitNet | - | - | - | - |
STDC | - | - | - | - |
GINet | ✔ | ✔ | - | - |
PointRend | ✔ | ✔ | - | - |
SegNet | - | - | - | - |
ESPNetV2 | - | - | - | - |
HRNetW48Contrast | - | - | - | ✔ |
DMNet | - | ✔ | - | - |
ESPNetV1 | - | - | - | - |
ENCNet | - | ✔ | - | - |
PFPNNet | - | ✔ | - | - |
FastFCN | ✔ | - | - | - |
BiSeNetV1 | - | - | - | - |
ENet | - | - | - | - |
CCNet | - | ✔ | - | - |
DDRNet | - | - | - | - |
GloRe | ✔ | - | - | - |
PP-LiteSeg | - | - | - | - |
Transformer series
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