PixDLM: A Dual-Path Multimodal Language Model for UAV Reasoning Segmentation
Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University（中国教育部多媒体可信感知与高效计算重点实验室，厦门大学）
Shuyan Ke, Yifan Mei, Changli Wu, Yonghan Zheng, Jiayi Ji, Liujuan Cao, Rongrong Ji
Reasoning segmentation has recently expanded from ground-level scenes to remote-sensing imagery, yet UAV data poses distinct challenges, including oblique viewpoints, ultra-high resolutions, and extreme scale variations. To address these issues, we formally define the UAV Reasoning Segmentation task and organize its semantic requirements into three dimensions: Spatial, Attribute, and Scene-level reasoning. Based on this formulation, we construct DRSeg, a large-scale benchmark for UAV reasoning segmentation, containing 10k high-resolution aerial images paired with Chain-of-Thought QA supervision across all three reasoning types. As a benchmark companion, we introduce PixDLM, a simple yet effective pixel-level multimodal language model that serves as a unified baseline for this task. Experiments on DRSeg establish strong baseline results and highlight the unique challenges of UAV reasoning segmentation, providing a solid foundation for future research.
Beihang University（北京航空航天大学）；Beijing Electronic Science and Technology Institute（北京电子科技学院）；Peng Cheng Laboratory（鹏城实验室）
Despite the growing number of unmanned aerial vehicles (UAVs) and aerial videos, there is a paucity of studies focusing on the aesthetics of aerial videos that can provide valuable information for improving the aesthetic quality of aerial photography. In this article, we present a method of deep multimodality learning for UAV video aesthetic quality assessment. More specifically, a multistream framework is designed to exploit aesthetic attributes from multiple modalities, including spatial appearance, drone camera motion, and scene structure. A novel specially designed motion stream network is…
MM-UAVBench: How Well Do Multimodal Large Language Models See, Think, and Plan in Low-Altitude UAV Scenarios?
Tsinghua University（清华大学）；Nankai University（南开大学）；Northwest Polytechnical University（西北工业大学）；Chinese Academy of Sciences（中国科学院）；Harbin Institute of Technology（哈尔滨工业大学）
UAV-CB: A Complex-Background RGB-T Dataset and Local Frequency Bridge Network for UAV Detection
Pengcheng Laboratory（鹏城实验室）；South China University of Technology（南方科技大学）；Peking University（北京大学）；Xinjiang University（新疆大学）；Harbin Institute of Technology（哈尔滨工业大学）
Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration
Department of Physics, J.K. Institute of Science（J.K.科学研究院物理系）；World Scientific University（世界科学大学）；University of Intelligent Studies（智能研究大学）；East China Normal University（华东师范大学）；Nanyang Technological University（南洋理工大学）；SenseTime Research（商汤科技研究院）；Shanghai Jiao Tong University（上海交通大学）；Harbin Institute of Technology（哈尔滨工业大学）
How Far are Modern Trackers from UAV-Anti-UAV? A Million-Scale Benchmark and New Baseline
Shanghai Jiao Tong University（上海交通大学）；Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；CloudWalk Technology Co., Ltd（云walk科技有限公司）；School of Artificial Intelligence, Shanghai Jiao Tong University（上海交通大学人工智能学院）；School of Aeronautics and Astronautics, Sun Yat-sen University（中山大学航空宇航学院）；Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）
Shanghai Jiao Tong University（上海交通大学）；CloudWalk Technology Co., Ltd（云从科技有限公司）；Shenzhen Research Institute of Big Data, the Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）深圳大数据研究院）；Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；JD Explore Academy in JD.com（京东集团京东探索研究院）；University of Sydney（悉尼大学）
Unmanned aerial vehicle (UAV) tracking is of great significance for a wide range of applications, such as delivery and agriculture. Previous benchmarks in this area mainly focused on small-scale tracking problems while ignoring the amounts of data, types of data modalities, diversities of target categories and scenarios, and evaluation protocols involved, greatly hiding the massive power of deep UAV tracking. In this work, we propose WebUAV-3M, the largest public UAV tracking benchmark to date, to facilitate both the development and evaluation of deep UAV trackers. WebUAV-3M contains over 3.3 …
From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping
University of Memphis（孟菲斯大学）；University of Missouri（密苏里大学）；University of Arkansas Division of Agriculture（阿肯色大学农业分部）；Mississippi State University（密西西比州立大学）
Centre for Research and Technology Hellas（希腊研究与技术中心）
In this work we consider UAVs as cooperative agents supporting human users in their operations. In this context, the 3D localisation of the UAV assistant is an important task that can facilitate the exchange of spatial information between the user and the UAV. To address this in a data-driven manner, we design a data synthesis pipeline to create a realistic multimodal dataset that includes both the exocentric user view, and the egocentric UAV view. We then exploit the joint availability of photorealistic and synthesized inputs to train a single-shot monocular pose estimation model. During trai…
No Labels, No Look-Ahead: Unsupervised Online Video Stabilization with Classical Priors
School of Electronic and Optical Engineering, Nanjing University of Science and Technology（南京理工大学电子与光学工程学院）；College of Geoexploration Science and Technology, Jilin University（吉林大学地球探测科学与技术学院）
UAUTrack: Towards Unified Multimodal Anti-UAV Visual Tracking
College of Intelligent Robotics and Advanced Manufacturing（智能机器人与先进制造学院）；Fudan University（复旦大学）；School of Computer Science and Technology（计算机科学与技术学院）；Zhejiang Normal University（浙江师范大学）；Department of Mechanical Engineering（机械工程系）；The Hong Kong Polytechnic University（香港理工大学）
UniRef-UAV: A Multimodal Benchmark for Universal Referring in UAV Imagery
School of Automation, Northwestern Polytechnical University（自动化学院，西北工业大学）；College of Missile Engineering, Rocket Force University of Engineering（导弹工程学院，火箭兵工程大学）；School of Artificial Intelligence, Chongqing University of Posts and Telecommunications（人工智能学院，重庆邮电大学）
UAVD-Mamba: Deformable Token Fusion Vision Mamba for Multimodal UAV Detection
College of Mechanical and Vehicle Engineering, Hunan University（湖南大学机械与车辆工程学院）；School of Electronic Information and Communications, Huazhong University of Science and Technology（华中科技大学电子信息与通信学院）
Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology
Institute of Artificial Intelligence, Beihang University（北京航空航天大学人工智能学院）；MMLab, CUHK（香港中文大学MMLab）；Centre for Perceptual and Interactive Intelligence（感知与交互智能中心）
UAV-Track VLA: Embodied Aerial Tracking via Vision-Language-Action Models
Beijing Institute of Technology（北京理工大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；University of Sanya（三亚学院）；Beijing University of Posts and Telecommunications（北京邮电大学）；Hunan University（湖南大学）；Beihang University（北京航空航天大学）；Flying Intelligence Team (Virtual Research Community)（飞行智能团队（虚拟研究社区））
A Multimodal Learning-based Approach for Autonomous Landing of UAV
Faculty of Engineering of University of Porto (FEUP)（波尔图大学工程学院）；Institute for Systems and Computer Engineering - Technology and Science (INESC TEC)（系统与计算机工程 - 技术与科学研究所）
EGM-Det: Entropy-Guided Multimodal Adaptive Fusion for UAV RGB-IR Object Detection
School of Cybersecurity, Northwestern Polytechnical University（西北工业大学网络空间安全学院）；School of Automation and Software Engineering, Shanxi University（山西大学自动化与软件学院）
FLORO: A Multimodal Geospatial Foundation Model for Ecological Remote Sensing Across Sensors and Scales
Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology（国王阿卜杜勒·阿齐兹科技大学生物与环境科学与工程 division）；Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology（国王阿卜杜勒·阿齐兹科技大学计算机、电气与数学科学与工程 division）
PRI-Net: A Lightweight Multimodal Framework for 3D UAV Localization
College of Information Science and Electronic Engineering, Zhejiang University（浙江大学信息与电子工程学院）；Zhejiang Key Laboratory of Multimodal Communication Networks and Intelligent Information Processing（浙江省多模态通信网络与智能信息处理重点实验室）
DRGBT-1K: A Large-scale High-quality Benchmark for Dynamic RGBT Tracking
Anhui University（安徽大学）；State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology（光电子信息采集与保护技术国家重点实验室）；Anhui Provincial Key Laboratory of Security Artificial Intelligence（安徽省安全人工智能重点实验室）；Anhui Provincial Key Laboratory of Multimodal Cognitive Computation（安徽省多模态认知计算重点实验室）
Large Language Model Guided Progressive Feature Alignment for Multimodal UAV Object Detection
School of Artificial Intelligence, Anhui University（安徽大学人工智能学院）；School of Computer Science and Technology, Anhui University（安徽大学计算机科学与技术学院）；University of Science and Technology of China（中国科学技术大学）
AeroGround: A Comprehensive Benchmark for Aerial-Ground Collaborative Reasoning
Shanghai Innovation Institute（上海创新研究院）；College of Future Information Technology, Fudan University（复旦大学未来信息技术学院）；College of Intelligent Robotics and Advanced Manufacturing, Fudan University（复旦大学智能机器人与先进制造学院）；Chongqing Technology and Business University（重庆工商大学）；The Chinese University of Hong Kong（香港中文大学）
A Multimodal Large Language Model-Driven Framework for Context-Aware UAV Emergency Landing Site Selection
School of Information Science and Engineering, Southeast University（信息科学与工程学院，东南大学）；LASER, International Digital Economy Academy（LASER，国际数字经济学院）；Department of Electronic Engineering, East China Normal University（电子工程系，华东师范大学）
MultiFly: A Real-World Multimodal Aerial Dataset with Annotation-Efficient Label Transfer and Cross-Modal Semantic Consistency
Fraunhofer Institute IVI（弗劳恩霍夫交通系统研究所）；Technical University of Munich（慕尼黑工业大学）；Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心）；University of Cambridge（剑桥大学）；Univ. of Applied Sciences Ingolstadt（英戈尔施塔特应用科学大学）
UAV (Unmanned Aerial Vehicles): Diverse Applications of UAV Datasets in Segmentation, Classification, Detection, and Tracking
Silicon Orchard Research and Analytics Lab（Silicon Orchard 研究与分析实验室）；Daffodil International University（水仙花国际大学）；BRAC University（BRAC 大学）；Texas Tech University（德克萨斯理工大学）；Clark Atlanta University（克拉克亚特兰大大学）
MambaTrack: Exploiting Dual-Enhancement for Night UAV Tracking
Cooperative Medianet Innovation Center（合作 medi 创新中心）；Shanghai Jiao Tong University（上海交通大学）；Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；CloudWalk Technology（云从科技）；Shanghai AI Laboratory（上海人工智能实验室）
Transmission Line Defect Detection Based on UAV Patrol Images and Vision-language Pretraining
Department of Electronic and Communication Engineering, North China Electric Power University（电子与通信工程系，华北电力大学）；Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University（河北省电力物联网技术重点实验室，华北电力大学）；Computer Science and Software Engineering Department, Monmouth University（计算机科学与软件工程系，蒙特莫恩大学）
FlightGPT: Towards Generalizable and Interpretable UAV Vision-and-Language Navigation with Vision-Language Models
School of Intelligent Systems Engineering, Sun Yat-Sen University（中山大学智能系统工程学院）；DP Technology（DP技术公司）；Beijing University Of Posts and Telecommunications（北京邮电大学）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；Tongji University（同济大学）；School of Integrated Innovation, Chulalongkorn University（朱拉隆功大学创新学院）
EgoSIS: From Factorized Visual Ego-Transitions to Motion-Canonical Spatial Evidence for UAV Reasoning
Beihang University（北京航空航天大学）；Zhongguancun Academy（中关村学院）；Northeastern University（东北大学）；Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences（中国科学院空间应用工程与技术中心）
Memory-Augmented Multimodal Large Language Models for Small Object Understanding in Streaming Aerial Videos
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；University of Freiburg（弗莱堡大学）；Hangzhou City University（杭州城市大学）；XGRIDS（XGRIDS公司）；Fudan University（复旦大学）；Hong Kong Baptist University（香港浸会大学）
AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration
Beijing University of Posts and Telecommunications（北京邮电大学）；QiYuanLab（启元实验室）；Tsinghua University（清华大学）；University of Electronic Science and Technology of China（电子科技大学）
ELDOR: A Dataset and Benchmark for Illegal Gold Mining in the Amazon Rainforest
Wake Forest University（威克森林大学）；City University of Hong Kong (Dongguan)（香港城市大学（东莞））；Duke University（杜克大学）；City University of Hong Kong（香港城市大学）；Yale University（耶鲁大学）；Alaska Spatial Science（阿拉斯加空间科学）；Colby College（科林斯学院）；Colby-Sawyer College（科林斯-萨威尔学院）；Lingnan University（岭南大学）；Centro de Innovación Cientifica Amazónica（亚马逊科学创新中心）
DynFly: Dynamic-Aware Continuous Trajectory Generation for UAV Vision-Language Navigation in Urban Environments
Beijing Institute of Technology（北京理工大学）；Tsinghua University（清华大学）；Dalian University of Technology（大连理工大学）；Xidian University（西安电子科技大学）；Huazhong University of Science and Technology（华中科技大学）
Advancing MLLM-based UAV Image Understanding and Reasoning: A Benchmark and a Training-Free Multi-Agent System
Fudan University（复旦大学）；College of Future Information Technology（未来信息技术学院）；Shanghai Innovation Institute（上海创新研究院）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；The Chinese University of Hong Kong（香港中文大学）
本研究构建UAVQA-Bench基准，识别MLLM用于无人机图像理解的三类失效模式，提出含DSPE、CAIR、DAAS的无训练多智能体系统UAV-MAS，其32B版本在基准上准确率超Gemini 3 Pro 4.0个百分点
LongFly: Long-Horizon UAV Vision-and-Language Navigation with Spatiotemporal Context Integration
School of Mechanical Engineering, Beijing Institute of Technology（北京理工大学机械工程学院）；Chongqing Innovation Center, Beijing Institute of Technology（北京理工大学重庆创新中心）；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）；Department of Automation, Tsinghua University（清华大学自动化系）；School of Software, Dalian University of Technology（大连理工大学软件学院）；School of Artificial Intelligence, Xidian University（西安电子科技大学人工智能学院）
RGBX-R1: Visual Modality Chain-of-Thought Guided Reinforcement Learning for Multimodal Grounding
School of Artificial Intelligence, Tianjin University（天津大学人工智能学院）；Low-Altitude Intelligence Lab, Xiong’an National Innovation Center（雄安国家创新中心低空智能实验室）；Xiong’an Guochuang Lantian Technology Co., Ltd.（雄安国创莲田科技有限公司）；College of Electronic Science and Technology, National University of Defense Technology（国防科技大学电子科学学院）
