https://cis.temple.edu/~jiewu/research/publications/Publication_files/MM_2025_UAV_CR.pdf
Abstract In UAV applications, dense haze severely obscures small ground-level objects, hindering the recovery of fine details. Existing visible-only dehazing methods struggle with such dense occlusions, while infrared imaging lacks color and fine texture information. To ad-dress these limitations, we propose the Haze Distribution-aware Cross-modal Fusion Network (HDCFN). HDCFN features two key ...