4 papers
Advancing All-Weather Building Damage Mapping to the Instance Level: Outcomes and Insights from the 2026 Bright Challenge
Hongruixuan Chen, He Huang, Haifeng Wang +19
Rapid post-disaster response requires timely, building-level information on whether structures remain intact, are damaged, or are destroyed. Post-event optical imagery, however, ma…
LRDUN: A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive Imaging
He Huang, Yujun Guo, Wei He
Deep unfolding networks (DUNs) have achieved remarkable success and become the mainstream paradigm for spectral compressive imaging (SCI) reconstruction. Existing DUNs are derived…
Building-Guided Pseudo-Label Learning for Cross-Modal Building Damage Mapping
Jiepan Li, He Huang, Yu Sheng +2
Accurate building damage assessment using bi-temporal multi-modal remote sensing images is essential for effective disaster response and recovery planning. This study proposes a no…
Degradation Alchemy: Self-Supervised Unknown-to-Known Transformation for Blind Hyperspectral Image Fusion
He Huang, Yong Chen, Yujun Guo +1
Hyperspectral image (HSI) fusion is an efficient technique that combines low-resolution HSI (LR-HSI) and high-resolution multispectral images (HR-MSI) to generate high-resolution H…