HazyDet

HazyDet is a large‑scale dataset created by the PLA Engineering University and other institutions, specifically for drone‑view object detection in haze and smog conditions. It contains 383,000 real‑world instances collected from natural haze environments and normal scenes where haze effects were artificially added to simulate adverse weather. The dataset creation combined depth estimation and atmospheric scattering models to ensure realism and diversity. HazyDet is primarily applied to object detection for drones operating under harsh weather, aiming to enhance drone perception in complex environments.