面向无人机的低空视觉数据集研究综述  

Research Review on Low-Altitude Visual Datasets for Unmanned Aerial Vehicles

作　　者：孙一铭 赵柯嘉 王硕 陈振国 阮媛 叶子凡 陈星睿 李欣 褚瑞麟 宋生敏 胡亦添 郭周鹏 王森 胡清华[2] 朱鹏飞[2] SUN Yiming;ZHAO Kejia;WANG Shuo;CHEN Zhenguo;RUAN Yuan;YE Zifan;CHEN Xingrui;LI Xin;CHU Ruilin;SONG Shengmin;HU Yitian;GUO Zhoupeng;WANG Sen;HU Qinghua;ZHU Pengfei(School of Automation,Southeast University,Nanjing 210096,China;College of Intelligence and Computing,Tianjin University,Tianjin 300354,China)

机构地区：[1]东南大学自动化学院,南京210096 [2]天津大学智能与计算学部,天津300354

出　　处：《数据采集与处理》2025年第2期274-302,共29页Journal of Data Acquisition and Processing

基　　金：新一代人工智能国家科技重大专项(2022ZD0116500);国家自然科学基金(62222608,62436002)。

摘　　要：在无人机技术与人工智能的跨域协同驱动下,依托国家低空经济政策与空域开放试点改革,低空视觉感知在智慧城市及巡检搜救等方面发挥了重要作用。高质量的低空视觉数据是低空智能感知领域的关键基础资源,公开数据集的发布与应用对低空感知技术的深入推进起到了重要作用。尽管已有大量面向低空视觉感知的数据集被提出,但对其系统化的整理与分析尚不充分。针对这一问题,本文全面调研了近11年间公开发布的低空无人机视觉相关数据集,基于不同的数据特征和应用场景对其进行分类探究,并选取具有代表性的数据集进行详细分析。本文涵盖了单机感知、多机协同感知、多任务感知、多源感知、复杂环境特性以及无人机具身智能等多个领域,为便于研究者理解与使用,本文以图表形式对所有数据集的基本信息进行了归纳总结,并从以下两个主要维度对其发展趋势进行了系统分析:(1)元数据分析,包括数据集规模分布、场景分布及支持任务类型等特点;(2)基本信息分析,涉及图像视频总量、目标类别分布和标注实例数量等关键指标。通过分析,充分展示了低空视觉感知数据集质量的显著进步,同时指出尽管已初步形成低空数据体系化架构,但是低空数据标注成本与效率失衡、多源数据复用性不足、极端环境覆盖薄弱以及具身智能数据割裂等问题依旧存在。最后,本文对低空数据集未来发展方向进行了展望。Driven by the cross⁃domain synergy of unmanned aerial vehicle(UAV)technology and artificial intelligence,and supported by national low⁃altitude economic policies and pilot reforms for airspace opening,the low⁃altitude visual perception has played a significant role in smart cities,inspection,rescue,and other applications.High⁃quality low⁃altitude visual data serve as the crucial foundational resource in the field of low⁃altitude intelligent perception,and the release and application of public datasets have been pivotal in advancing low⁃altitude perception technologies.Despite the proposal of numerous datasets for low⁃altitude visual perception,systematic organization and analysis of these datasets remain inadequate.To address this issue,this paper conducts a comprehensive survey of publicly released low⁃altitude UAV vision⁃related datasets over the past 11 years,categorizes and explores them based on different data characteristics and application scenarios,and selects representative datasets for detailed analysis.This review covers multiple domains,including single⁃UAV perception,multi⁃UAV cooperative perception,multi⁃task perception,multi⁃source perception,complex environmental characteristics,and UAV embodied intelligence.To facilitate researchers’understanding and use,the paper summarizes the basic information of all datasets in graphical form and systematically analyzes their development trends from two main dimensions:(1)metadata analysis,including dataset size distribution,scenario distribution,and supported task types;and(2)basic information analysis,involving total image and video counts,target category distribution,and annotation instance numbers.The analysis fully demonstrates the significant progress in the quality of low⁃altitude visual perception datasets.Meanwhile,it points out that,despite the initial formation of a systematic framework for low⁃altitude data,issues such as the imbalance between cost and efficiency in low⁃altitude data annotation,insufficient reus

关 键 词：低空应用 多机协同 多源感知 多任务感知 无人机具身智能 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]