UW-Bench
The UW‑Bench dataset, created by the School of Microelectronics and Communication Engineering at Chongqing University, focuses on urban flood detection, containing 7,677 annotated images sourced from surveillance cameras and handheld devices. The dataset was collected under various adverse conditions such as low light, strong reflections, and clear water, aiming to improve model generalization in real‑world applications. Manual annotation ensures data quality, suitable for enhancing accuracy and efficiency of urban flood detection.
Dataset description and usage context
Urban Flood Detection Dataset (UW‑Bench)
Overview
- Dataset Name: Urban Waterlogging Benchmark (UW‑Bench)
- Purpose: For urban flood detection, especially under diverse and adverse environmental conditions.
- Features: Includes regular samples and challenging samples to objectively assess model capability in real‑world scenarios.
Details
- Training Set: Collected and annotated by the LiVE team at Chongqing University.
- Test Set: Provided by Huawei.
- Dataset Links:
- Training set: Baidu Drive | Google Drive
Citation
@inproceedings{ song2024lsmadapter, title={Urban Waterlogging Detection: A Challenging Benchmark and Large‑Small Model Co‑Adapter}, author={Suqi Song and Chenxu Zhang and Peng Zhang and Pengkun Li and Fenglong Song and Lei Zhang}, journal = {ECCV}, issue_date = {2024} }
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