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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.CV2026

GeoSeg-OV: Bridging Geospatial Gaps with Structural Guidance for Open-Vocabulary Remote Sensing Segmentation

Ruizhong Liu, Tingzhang Luo, Zaiyan Zhang +4

Open-vocabulary remote sensing segmentation has recently emerged as a promising paradigm that enables pixel-level recognition of arbitrary categories specified by natural language,…

cs.CV2026

CoRE-UIR: Prior-guided common and residual experts for efficient all-in-one remote sensing image restoration

Zaiyan Zhang, Qiangqiang Yuan, Jie Li +5

The paper introduces CoRE-UIR, a prior‑guided framework that separates restoration into a common dense expert and low‑rank residual experts to efficiently handle multiple degradati…

cs.CV2026

SemDINO: Foundation Prior-Guided Cross-Temporal Semantic Alignment Network for Remote Sensing Change Detection

Xinyu Tong, Meihua Zhou, Jinxiao Sun +4

Semantic change detection (SCD) in remote sensing aims to identify land-cover transitions between bi-temporal observations while suppressing pseudo-changes caused by illumination v…

cs.CV2026

Task-Driven Prompt Learning: A Joint Framework for Multi-modal Cloud Removal and Segmentation

Zaiyan Zhang, Jie Li, Shaowei Shi +1

Optical remote sensing imagery is indispensable for Earth observation, yet persistent cloud occlusion limits its downstream utility. Most cloud removal (CR) methods are optimized f…

cs.CV2024

Multi-scale Restoration of Missing Data in Optical Time-series Images with Masked Spatial-Temporal Attention Network

Zaiyan Zhang, Jining Yan, Yuanqi Liang +3

Remote sensing images often suffer from substantial data loss due to factors such as thick cloud cover and sensor limitations. Existing methods for imputing missing values in remot…