CASS: Class-wise Adaptive Strategy for Semi Supervised Semantic Segmentation

Update Note

• (24.01.31) The paper has been accepted into IEEE Access.

Paper

Getting Started

PASCAL VOC 2012 download link : JPEGImages, SegmentationClass

[Your Pascal Path]
  ├── JPEGImages
  └── SegmentationClass

Pretrained Backbone : ResNet101, MiT-B4

Eval Weight : link

CASS
├── pretrained
│   ├── resnet101.pth
│   └── mit_b4.pth
└── cass_pretrained
    ├── 1_CASS_1_4_resnet101_78.04.pth
    ├── 2_CASS_1_4_resnet101_78.32.pth
    ├── 3_CASS_1_4_resnet101_78.05.pth
    ├── 1_CASS_1_4_segf_b4_79.90.pth
    ├── 2_CASS_1_4_segf_b4_79.81.pth
    └── 3_CASS_1_4_segf_b4_79.99.pth

Config

You can control our methods in the config file.

Train

sh tool/train.sh <num_gpu> <port>

# ex : sh tool/train.sh 4 23500

Eval

sh tool/eval.sh <num_gpu> <port>

# ex : sh tool/eval.sh 4 23500

Paper Result

Method	1/2 (5292)	1/4 (2646)	1/8 (1323)	1/16 (662)
ST++	-	76.6	76.3	74.5
UniMatch	77.5	77.2	77.0	76.5
CASS-V3(ours)	78.1	78.0	77.5	77.1
CASS-B4(ours)	80.2	79.9	78.8	77.5

Re Implementation Result

Model	1/2 (5291)	1/4 (2646)	1/8 (1323)	1/16 (662)
CASS-V3 (Try 1)	78.86	78.04	77.18	TODO
CASS-V3 (Try 2)	78.60	78.32	77.29	TODO
CASS-V3 (Try 3)	79.21	78.05	77.76	TODO
Mean (std)	78.89 (0.25)	78.13 (0.13)	77.41 (0.25)	TODO
CASS-B4 (Try 1)	80.49	79.90	78.78	TODO
CASS-B4 (Try 2)	80.53	79.81	78.72	TODO
CASS-B4 (Try 3)	80.42	79.99	78.76	TODO
Mean (std)	80.48 (0.05)	79.89 (0.07)	78.75 (0.02)	TODO