21 citations · 33 across the 11 of their papers we have counts for
12 papers
SPEANet: Structural Prior Enhanced Attention Network for Parameter-Efficient Remote Sensing Object Detection
Wei Lu, Junjie Li, Feifei Sang +1
Remote sensing object detection (RSOD) requires compact backbones capable of preserving weak geometric cues under extreme scale variation and background clutter. Fixed structural o…
AeroLLE: Constrained Pseudo-Supervision for Nighttime Aerial Image Enhancement with the AeroNight-1.5K Benchmark
Wei Lu, Hongyuan Liu, Si-Bao Chen
Nighttime aerial image enhancement is challenged by spatially nonuniform exposure, mixed illumination, and weak structural evidence, while registered normal-light targets are diffi…
BRIC-Net: Boundary-Reliable Illumination-Color Interaction for Remote Sensing Image Deshadowing
Wei Lu, Yi Liu, Si-Bao
Shadows in remote sensing images obscure surface appearance and disrupt radiometric continuity, reducing the reliability of visual interpretation and downstream analysis. Remote se…
SARU: A Shadow-Aware and Removal Unified Framework for Remote Sensing Images with New Benchmarks
Zi-Yang Bo, Wei Lu, Hongruixuan Chen +2
Shadows are a prevalent problem in remote sensing imagery (RSI), degrading visual quality and severely limiting the performance of downstream tasks like object detection and semant…
AeroDeshadow: Physics-Guided Shadow Synthesis and Penumbra-Aware Deshadowing for Aerospace Imagery
Wei Lu, Zi-Yang Bo, Fei-Fei Sang +3
Shadows are prevalent in high-resolution aerospace imagery (ASI). They often cause spectral distortion and information loss, which degrade downstream interpretation tasks. While de…
Multi-Modal Building Change Detection for Large-Scale Small Changes: Benchmark and Baseline
Ye Wang, Wei Lu, Zhihui You +6
Change detection in optical remote sensing imagery is susceptible to illumination fluctuations, seasonal changes, and variations in surface land-cover materials. Relying solely on…
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,…
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…
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…
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…
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…
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…