6 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
CityToolVQA: Tool-Augmented Visual Question Answering for 3D Spatial Cognition in Urban Low-Altitude Environments
Boao Yu, Yingzhen Nie, Yue Hu +2
CityToolVQA addresses the weak performance of Vision-Language Models (VLMs) on quantitative tasks in urban low-altitude visual question answering. We divide the seven tasks into qu…
Towards Embodied Air-Ground Cooperative Object Search: Benchmark, Dataset and Agentic Method
Boao Yu, Zimo Chen, Junreng Rao +4
Air-Ground Object Search (AGOS) in urban environments is a challenging embodied task, which requires an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) to jointl…
Map the Possibilities: Spatial Belief Fields for Language-Goal Aerial Navigation
Haotian Xu, Yue Hu, Zhengqiu Zhu +3
Language-goal aerial navigation requires an agent to local- ize a potentially unobserved target from relational instruc- tions and partial observations, and translate this inferenc…
ScoutVLA: UAV-Centric Active Perception via a Dual-Expert VLA Model for Open-World Embodied Question Answering
Wenhao Lu, Zhengqiu Zhu, Xiaofeng Wang +7
Aerial Embodied Question Answering (EQA) requires Unmanned Aerial Vehicles (UAVs) to actively perceive the environment and answer natural language questions. Existing outdoor EQA s…
CityCube: Benchmarking Cross-view Spatial Reasoning on Vision-Language Models in Urban Environments
Haotian Xu, Yue Hu, Zhengqiu Zhu +7
Cross-view spatial reasoning is essential for embodied AI, underpinning spatial understanding, mental simulation and planning in complex environments. Existing benchmarks primarily…
Towards Autonomous UAV Visual Object Search in City Space: Benchmark and Agentic Methodology
Yatai Ji, Zhengqiu Zhu, Yong Zhao +7
Aerial Visual Object Search (AVOS) tasks in urban environments require Unmanned Aerial Vehicles (UAVs) to autonomously search for and identify target objects using visual and textu…