Condition-Embedded Visible-Infrared image dataset for typical ground features

Infrared imaging is significantly influenced by weather, temperature and humidity, indicating notable differences in infrared characteristics for the same scene under varying weather conditions. Therefore, studying translation from visible light images to infrared images must consider the conditional information. However, existing visible-light-infrared image datasets do not account for conditional information. This dataset rigorously records imaging condition information. From 2022 to 2024, it has accumulated 22,435 pair data with condition information from multiple regions, covering five kinds of weather including cloudy, sunny, rainy, snowy, and foggy. The scenes include eight typical ground features such as water, forest, grassland, beach, farmland, buildings, roads, and bare land. It accurately records information such as temperature, humidity etc. at the moment of data collection. This dataset provides data support for studying the precise translation between visible light and infrared images.