3 papers
cs.CV2026
ReDiS: Reasoning-Diagnosis Self-Evolution for Multimodal Reasoning in Remote Sensing
Yi Liu, Wentao Jiang, Shuo Ni +5
Multimodal large language models (MLLMs) have shown strong potential for remote sensing understanding, yet reliable reasoning remains challenging when tasks require fine-grained vi…
cs.CV2026
UHR-Micro: Diagnosing and Mitigating the Resolution Illusion in Earth Observation VLMs
Shuo Ni, Tong Wang, Jing Zhang +5
Vision-Language Models (VLMs) are increasingly used to analyze ultra-high-resolution (UHR) Earth observation imagery, yet they face a severe scale mismatch between broad scene cont…
cs.CV2025
UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes
Shuo Ni, Di Wang, He Chen +3
Instruction-driven segmentation in remote sensing generates masks from guidance, offering great potential for accessible and generalizable applications. However, existing methods s…