Woven Fabric Defect Detection
WFDD is a dataset for benchmarking anomaly detection methods with a focus on textile inspection. It includes 4101 woven fabric images categorized into 4 categories: grey cloth, grid cloth, yellow cloth, and pink flower. The first three classes are collected from the industrial production sites of WEIQIAO Textile, while the 'pink flower' class is gathered from the publicly available Cloth Flaw Dataset. Each category contains block-shape, point-like, and line-type defects with pixel-level annotations.
Variants: WFDD
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Anomaly Detection | GLASS | A Unified Anomaly Synthesis Strategy … | 2024-07-12 |
Recent papers with results on this dataset: