collaborators

6 papers

cs.CV2026

UniRoute: Unified Routing Mixture-of-Experts for Modality-Adaptive Remote Sensing Change Detection

Qingling Shu, Sibao Chen, Wei Lu +2

Current remote sensing change detection (CD) methods mainly rely on specialized models, which limits the scalability toward modality-adaptive Earth observation. For homogeneous CD,…

cs.CV2025

Unsupervised Ultra-High-Resolution UAV Low-Light Image Enhancement: A Benchmark, Metric and Framework

Wei Lu, Lingyu Zhu, Si-Bao Chen

Low light conditions significantly degrade Unmanned Aerial Vehicles (UAVs) performance in critical applications. Existing Low-light Image Enhancement (LIE) methods struggle with th…

cs.CV2025

Semantic Change Detection of Roads and Bridges: A Fine-grained Dataset and Multimodal Frequency-driven Detector

Qingling Shu, Sibao Chen, Xiao Wang +4

Accurate detection of road and bridge changes is crucial for urban planning and transportation management, yet presents unique challenges for general change detection (CD). Key dif…

cs.CV2025

Real-World Remote Sensing Image Dehazing: Benchmark and Baseline

Zeng-Hui Zhu, Wei Lu, Si-Bao Chen +3

Remote Sensing Image Dehazing (RSID) poses significant challenges in real-world scenarios due to the complex atmospheric conditions and severe color distortions that degrade image…

cs.CV2025

LEGNet: A Lightweight Edge-Gaussian Network for Low-Quality Remote Sensing Image Object Detection

Wei Lu, Si-Bao Chen, Hui-Dong Li +4

Remote sensing object detection (RSOD) often suffers from degradations such as low spatial resolution, sensor noise, motion blur, and adverse illumination. These factors diminish f…

cs.CV2025

LWGANet: Addressing Spatial and Channel Redundancy in Remote Sensing Visual Tasks with Light-Weight Grouped Attention

Wei Lu, Xue Yang, Si-Bao Chen

Light-weight neural networks for remote sensing (RS) visual analysis must overcome two inherent redundancies: spatial redundancy from vast, homogeneous backgrounds, and channel red…