We integrate a novel few-shot segmentation dataset （FSSD-12）of pure strip steel surface defect, including 12 different surface defects of strip steel.

We propose a few-shot semantic segmentation method named cross position aggregation network (CPANet) to solve the number of strip steel surface defect is deficient and the ground truth is difficultly labeled.

The dataset and code are available at:https://pan.baidu.com/s/1_BORNJrO4msD0OPEcVSc-Q?pwd=9m10

https://ieeexplore.ieee.org/document/10049179

2023-Cross Position Aggregation Network for Few-Shot Strip Steel Surface Defect Segmentation.pdf

H. Feng, K. Song, W. Cui, Y. Zhang and Y. Yan, "Cross Position Aggregation Network for Few-shot Strip Steel Surface Defect Segmentation," in IEEE Transactions on Instrumentation and Measurement, doi: 10.1109/TIM.2023.3246519.

[1] TGRNet： Triplet-graph reasoning network for few-shot metal generic surface defect segmentation

The dataset and code are available at:https://pan.baidu.com/s/1dEai3yXrFOsuWcQ5mkE7_A?pwd=qzo6

[1] FSC-20 dataset & FaNet The dataset and code are available at:https://github.com/VDT-2048/FSC-20

[2] MSD-Cls dataset & GTnet The dataset and code are available at:https://github.com/successhaha/GTnet