most citedMT-CYP-Net: Multi-Task Network for Pixel-Level Crop Yield Prediction Under Very Few Samples

7 citations · 7 across the 15 of their papers we have counts for

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cs.CV2026

DIAL: Dynamic and Informed Adjustment of the Native Stochastic Law for Reliable Weather Ensembles

Yucheng Wang, Haonan Guo, Tianhao Zhao +4

Ensemble weather forecasts can look reliable in global averages while hiding too little spread in some cases and too much in others. These errors vary across variables, spatial sca…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

RSVideo: Are Your Vision-Language Models Ready for Remote Sensing Videos?

Hongjie Zhou, Shiqin Wang, Haoyang Chen +5

Remote-sensing videos enable real-time observation of changes in target attributes, short-term activities, and scene evolution. They record motion, actions, interactions, and scene…

cs.CV2026

PNEC-Mamba: Prototype-Guided Positive-Negative Evidence Calibration for Hyperspectral Image Classification

Mingzhen Xu, Can Xu, Di Wang +2

In real-world hyperspectral scenes, pixel representations are often ambiguous due to factors such as spectral similarity, mixed pixels, and local context interference, which may si…

cs.CV2026

MBTI: A Multi-Branch Efficient Fine-Tuning Framework for Hyperspectral Image Classification with Foundation Models

Mingzhen Xu, Haonan Guo, Di Wang +9

Hyperspectral foundation models learn transferable spectral-spatial representations from large-scale unlabeled data. They provide an effective paradigm for adapting to downstream h…

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.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

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…

cs.CV2025

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…

cs.CV2025

Residual Diffusion Bridge Model for Image Restoration

Hebaixu Wang, Jing Zhang, Haoyang Chen +4

Diffusion bridge models establish probabilistic paths between arbitrary paired distributions and exhibit great potential for universal image restoration. Most existing methods mere…

cs.CV2025★ 7 cited

MT-CYP-Net: Multi-Task Network for Pixel-Level Crop Yield Prediction Under Very Few Samples

Shenzhou Liu, Di Wang, Haonan Guo +2

Accurate and fine-grained crop yield prediction plays a crucial role in advancing global agriculture. However, the accuracy of pixel-level yield estimation based on satellite remot…

cs.CV2025

DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restoration

Hebaixu Wang, Jing Zhang, Haonan Guo +3

Diffusion models have achieved remarkable progress in universal image restoration. While existing methods speed up inference by reducing sampling steps, substantial step intervals…