Benchmarking Multi-Scene Fire and Smoke Detection

被引:0
|
作者
Han, Xiaoyi [1 ]
Pu, Nan [2 ]
Feng, Zunlei [1 ,3 ]
Bei, Yijun [1 ]
Zhang, Qifei [1 ]
Cheng, Lechao [4 ]
Xue, Liang [5 ]
机构
[1] Zhejiang Univ, Sch Software Technol, Hangzhou, Peoples R China
[2] Univ Trento, Trento, Italy
[3] Zhejiang Univ, Minist Educ & Microsoft, Key Lab Visual Percept, Hangzhou, Peoples R China
[4] Hefei Univ Technol, Hefei, Peoples R China
[5] Suzhou City Univ, Suzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Fire and Smoke Detection; The Multi-Scene Fire and Smoke Detection Benchmark;
D O I
10.1007/978-981-97-8795-1_14
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 https://xiaoyihan6.github.io/FSD/.
引用
收藏
页码:203 / 218
页数:16
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