Abstract
Existing multimodal image fusion (MMIF) datasets lack comprehensive coverage of adverse weather conditions. To address this limitation, we introduce AWMM-100K, a large-scale benchmark dataset constructed from RoadScene, MSRS, M3FD, and LLVIP, followed by controlled degradation processes to simulate rain, haze, and snow.
In addition, real-world data were captured using a DJI M30T drone equipped with high-resolution visible and thermal cameras. AWMM-100K contains over 187,699 images with weather conditions categorized into light, medium, and heavy intensities. The dataset supports research on multimodal image fusion as well as image restoration tasks such as dehazing, deraining, and desnowing.
Dataset Overview
Image Fusion
Image Restoration
Real Scene
Compound Degradation
