Multi-Scene Fire and Smoke Detection Benchmark (MS-FSDB)
Multi‑Scene Fire and Smoke Detection Benchmark (MS‑FSDB) is a comprehensive and fine‑grained fire and smoke detection benchmark created by Zhejiang University. The dataset contains 12,586 images depicting 2,731 scenes, comprising 3,603 positive samples and 8,983 negative samples. The creation process involved systematic collection of diverse resources from public sources, followed by scene expansion and re‑annotation to ensure data accuracy and consistency. MS‑FSDB includes not only flame detection but also smoke detection tasks, applicable to various complex indoor and outdoor scenarios, and aims to provide strong support for breakthroughs and development in fire detection technology.
Dataset description and usage context
Multi‑Scene Fire and Smoke Detection Benchmark
Dataset Overview
- Dataset Name: Multi-Scene Fire and Smoke Detection (FSD) Benchmark
- Dataset Type: Includes five previously existing FSD datasets and a new test set
- Dataset Processing: Reprocessed the previous FSD datasets, unifying the label format across all datasets
Dataset Usage
- Usage: Benchmark testing for multi‑scene fire and smoke detection
Dataset Source
- Source: Created by Xiaoyi Han, Nan Pu, Zunlei Feng, Yijun Bei, Qifei Zhang, Lechao Cheng, Liang Xue and others
- Institutions: Zhejiang University, University of Trento, Hefei University of Technology, Suzhou City University
Dataset Release
- Release Status: Paper accepted by PRCV 2024; code release scheduled for after July 10
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