collaborators

6 papers

cs.CV2026

GRASP: Granularity-Aware Region Alignment and Semantic Prototype Learning for Fine-Grained Cross-Modal Understanding in Drone Views

Jiahui Cui, Yan Zhao, Kan Wei +4

Fine-grained cross-modal understanding in drone views is essential for aerial vision-language navigation. However, the inherent wide field of view and overhead perspective of drone…

cs.CV2026

GeoSearcher: Anchor-Guided Progressive Reasoning for Remote Sensing Visual Grounding with Process Supervision

Dianyu Wang, Peirong Zhang, Xuyang Li +2

Recent multimodal large language models (MLLMs) have shown strong cross-modal understanding and coordinate generation abilities in visual grounding. However, transferring these abi…

cs.CV2026

MotionScape: A Large-Scale Real-World Highly Dynamic UAV Video Dataset for World Models

Zile Guo, Zhan Chen, Enze Zhu +4

Recent advances in world models have demonstrated strong capabilities in simulating physical reality, making them an increasingly important foundation for embodied intelligence. Fo…

cs.IR2026

MARA: A Multimodal Adaptive Retrieval-Augmented Framework for Document Question Answering

Hui Wu, Haoquan Zhai, Yuchen Li +8

Retrieval-based multimodal document QA aims to identify and integrate relevant information from visually rich documents with complex multimodal structures. While retrieval-augmente…

cs.CV2025

RAPTOR: Real-Time High-Resolution UAV Video Prediction with Efficient Video Attention

Zhan Chen, Zile Guo, Enze Zhu +4

Video prediction is plagued by a fundamental trilemma: achieving high-resolution and perceptual quality typically comes at the cost of real-time speed, hindering its use in latency…

cs.CV2025

GeoViS: Geospatially Rewarded Visual Search for Remote Sensing Visual Grounding

Peirong Zhang, Yidan Zhang, Luxiao Xu +6

Recent advances in multimodal large language models(MLLMs) have led to remarkable progress in visual grounding, enabling fine-grained cross-modal alignment between textual queries…