Knowing the Self, Understanding the World: A Dual-Cognition Benchmark for UAV Spatio-temporal Reasoning with MLLMs
Multimodal large language models have achieved strong performance across diverse vision-language tasks, yet their capabilities in UAV scenarios remain insufficiently explored. Recent UAV-oriented benchmarks have begun to evaluate MLLMs in aerial scenarios, but they typically focus on scene understanding, event recognition, or navigation completion, rather than jointly assessing the dual-cognition capability required for UAV agents: reasoning about both the UAV's own state and the external environment in multiview spatio-temporal contexts. To address this gap, we present UAV-DualCog, a benchmark for aerial multiview spatio-temporal reasoning built on this dual-cognition perspective. UAV-Du...
| Authors | Like Liu, Zhengzheng Xu, Haitao He et al. |
|---|---|
| Primary category | cs.CV |
| Published | 17 July 2026 |
| Last updated at source | 17 July 2026 |
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- Lozumi/UAV-DualCogDataset · cited by
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- Lozumi/UAV-DualCogDataset
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