5 papers
Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?
Qiwei Ma, Chunping Qiu, Xinjun Cheng +5
The rapid development of multimodal large language models (MLLMs) has introduced a flexible paradigm for remote sensing image scene understanding (RSISU), enabling natural-language…
Not All Patches are Equal: Sampling Matters for Visible-Infrared Pre-Training
Qiwei Ma, Bin Deng, Junjie Zhu +5
Visible-infrared (VIS-IR) alignment is a key pre-training task for robust multi-sensor perception. Most existing methods use uniform patch-wise contrastive learning, but this can b…
Topology-Aware Skeleton Detection via Lighthouse-Guided Structured Inference
Daoyong Fu, Xiang Zhang, Zhaohuan Zhan +2
In natural images, object skeletons are used to represent geometric shapes. However, even slight variations in pose or movement can cause noticeable changes in skeleton structure,…
SAR-TEXT: A Large-Scale SAR Image-Text Dataset Built with SAR-Narrator and A Progressive Learning Strategy for Downstream Tasks
Yiguo He, Xinjun Cheng, Junjie Zhu +5
Vision Language Models (VLMs) have achieved remarkable breakthroughs in the field of remote sensing in recent years. Synthetic Aperture Radar (SAR) imagery, with its all-weather ca…
Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation
Yiguo He, Junjie Zhu, Yiying Li +5
The application of Vision-language foundation models (VLFMs) to remote sensing (RS) imagery has garnered significant attention due to their superior capability in various downstrea…