12 papers
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…
Hallucination-aware Faithful Reasoning in Remote Sensing
Yi Liu, Jing Zhang, Xiang Feng +5
Multimodal large language models (MLLMs) have demonstrated promising capabilities for remote sensing reasoning, yet they frequently generate visually unsupported reasoning that con…
OmniRSI: Taming Latent Diffusion for Unified Multimodal Remote Sensing Image Generation
Hebaixu Wang, Jing Zhang, Haonan Guo +3
Multimodal remote sensing image generation emerges as a promising paradigm for recovering complete and complementary observations from heterogeneous and partially observed remote s…
Seeing Clearly without Training: Mitigating Hallucinations in Multimodal LLMs for Remote Sensing
Yi Liu, Jing Zhang, Di Wang +3
Multimodal large language models (MLLMs) suffer from pronounced hallucinations in remote sensing visual question-answering (RS-VQA), primarily caused by visual grounding failures i…
Any2Any: Unified Arbitrary Modality Translation for Remote Sensing
Haoyang Chen, Jing Zhang, Hebaixu Wang +7
Multi-modal remote sensing imagery provides complementary observations of the same geographic scene, yet such observations are frequently incomplete in practice. Existing cross-mod…
Universal Pansharpening Model
Hebaixu Wang, Jing Zhang, Haonan Guo +4
Pansharpening generates the high-resolution multi-spectral (MS) image by integrating spatial details from a texture-rich panchromatic (PAN) image and spectral attributes from a low…
VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing
Zhiming Luo, Di Wang, Haonan Guo +2
Recent advancements in Multimodal Large Language Models (MLLMs) have enabled complex reasoning. However, existing remote sensing (RS) benchmarks remain heavily biased toward percep…
Degradation-Aware Metric Prompting for Hyperspectral Image Restoration
Binfeng Wang, Di Wang, Haonan Guo +2
Unified hyperspectral image (HSI) restoration aims to recover diverse degradations within a single model. However, current methods often rely on impractical explicit priors or opaq…
SARMAE: Masked Autoencoder for SAR Representation Learning
Danxu Liu, Di Wang, Hebaixu Wang +6
Synthetic Aperture Radar (SAR) imagery plays a critical role in all-weather, day-and-night remote sensing applications. However, existing SAR-oriented deep learning is constrained…
GeoBridge++: Fact-Guided Geo-Semantic Bridging for Unified Cross-View Geo-Localization
Zixuan Song, Jing Zhang, Di Wang +7
Cross-view geo-localization infers a location by retrieving geo-tagged reference images matching a query image. However, the traditional satellite-centric paradigm limits robustnes…
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…
GeoZero: Incentivizing Reasoning from Scratch on Geospatial Scenes
Di Wang, Shunyu Liu, Wentao Jiang +10
Multimodal large language models (MLLMs) have undergone rapid development in advancing geospatial scene understanding. Recent studies have sought to enhance the reasoning capabilit…