构建标准化火灾烟雾检测基准，推动真实场景下技术发展。
Benchmarking Multi-Scene Fire and Smoke Detection
- 整合多源数据并统一标注规范，形成标准化检测平台。
- 扩展覆盖场景，提升数据集对真实环境的代表性。
- 适合火灾检测研究者、智能安防开发者参考使用。
现有公开火灾烟雾检测（FSD）数据集存在不一致性，已成为技术进步的瓶颈。深入分析发现，核心问题在于缺乏标准化的数据集构建、统一的评估体系和明确的性能基准。为此，我们系统收集公共资源，创建更全面、精细的FSD基准。针对现有数据集场景覆盖不足的问题，我们有策略地扩展场景，重新标注并标准化已有公开数据集，确保准确性和一致性。目标是建立一个标准化、真实、统一且高效的FSD研究平台，紧密贴近实际应用场景。本项目旨在为FSD技术的突破与发展提供坚实支持。项目地址：https://xiaoyihan6.github.io/FSD/
原文摘要 · Abstract (English)
The current irregularities in existing public Fire and Smoke Detection (FSD) datasets have become a bottleneck in the advancement of FSD technology. Upon in-depth analysis, we identify the core issue as the lack of standardized dataset construction, uniform evaluation systems, and clear performance benchmarks. To address this issue and drive innovation in FSD technology, we systematically gather diverse resources from public sources to create a more comprehensive and refined FSD benchmark. Additionally, recognizing the inadequate coverage of existing dataset scenes, we strategically expand scenes, relabel, and standardize existing public FSD datasets to ensure accuracy and consistency. We aim to establish a standardized, realistic, unified, and efficient FSD research platform that mirrors real-life scenes closely. Through our efforts, we aim to provide robust support for the breakthrough and development of FSD technology. The project is available at \href{https://xiaoyihan6.github.io/FSD/}{https://xiaoyihan6.github.io/FSD/}.
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