USD: Underwater Structure Defect Dataset with Suspended Impurities

The USD dataset is designed for underwater structure surface defect detection under suspended-impurity interference. It consists of four subsets: USD-SSI, USD-RSI, USD-VDO, and USD-VDW. USD-SSI contains 16 sets of underwater structure videos with synthetically generated suspended impurities. Impurity samples of diverse sizes, shapes, and colors were extracted from real underwater footage and inserted into original videos using a custom random motion generation program. Corresponding impurity mask videos and manually labeled defect annotations are provided. USD-RSI comprises 14 sets of real-world underwater structural videos containing naturally occurring suspended impurities, providing a benchmark for evaluating detection algorithms under realistic underwater conditions. USD-VDO is an annotated underwater structure defect dataset containing 541 images without suspended impurities, along with manually labeled ground truth annotations of defects. USD-VDW consists of 70 frame sets randomly selected from USD-RSI. It includes corresponding E-procedure processed results and manually labeled defect ground truth, making it suitable for evaluating the complete E-D cascaded framework. The dataset can be used for suspended impurity localization, underwater structure defect detection, defect segmentation, and evaluation of robust visual perception methods under complex underwater environments. GitHub repository: https://github.com/your-username/USD-Dataset