MLRSNet is a large-scale, high-resolution, multi-label remote sensing dataset for semantic scene understanding. The dataset contains 109,161 high-resolution remote sensing images that are annotated into 46 categories, and the number of sample images in each category ranges from 1,500 to 3,000. The images have a fixed size of 256×256 pixels with various pixel resolutions.

In addition, each image in the dataset is labeled with several of the 60 predefined class labels, and the number of labels associated with each image ranges from 1 to 13. This dataset can be used for multi-label based image classification, multi-label based image retrieval, and image segmentation.