FMB Dataset (Full-time Multi-modality Benchmark Dataset)

FMB contains 1500 well-registered infrared and visible image pairs with 14 annotated pixel-level categories. Also, it covers a wide range of pixel variations and various severe environments, e.g., dense fog, heavy rain, and low-light condition. The FMB dataset includes rich scenes under different illumination conditions, so that it enables fusion/segmentation model to improve the generalization ability greatly. We labeled 98.16% of all pixels into 14 different categories including Road, Sidewalk, Building, Traffic Light, Traffic Sign, Vegetation, Sky, Person, Car, Truck, Bus, Motorcycle, Bicycle and Pole, which often appear in real world automatic driving and semantic understanding tasks.

FMB数据集包含1500对配准精度优异的红外与可见光图像对，共涵盖14个像素级标注类别。该数据集覆盖了丰富的像素变化场景与多种极端环境，例如浓雾、暴雨及低光照条件。FMB数据集包含不同光照条件下的多样场景，可助力融合/分割模型大幅提升泛化能力。我们将全部像素中的98.16%标注为14个不同类别，涵盖道路、人行道、建筑物、交通信号灯、交通标志、植被、天空、行人、轿车、卡车、巴士、摩托车、自行车及杆体（Pole），这些类别均常见于真实世界的自动驾驶与语义理解任务中。