FAIR1M is a large-scale dataset for fine-grained object detection and recognition in remote sensing images. To meet the needs of practical applications, images in the FAIR1M dataset are collected from different sensors and platforms, with a spatial resolution ranging from 0.3m to 0.8m. There are more than 1 million instances and more than 40,000 images in this dataset. All objects in the FAIR1M dataset are annotated with respect to 5 categories and 37 sub-categories by oriented bounding boxes. Each image is of the size in the range from 600 to 10,000 pixels and contains objects exhibiting a wide variety of scales, orientations, and shapes.