LIB-HSI: RGB and Hyperspectral images of Building Facades

The LIB-HSI dataset contains hyperspectral reflectance images and their corresponding RGB images of building façades in a light industrial environment. The dataset also contains pixel-level annotated images for each hyperspectral/RGB image. The LIB-HSI dataset was created to develop deep learning methods for segmenting building facade materials.\n\nThe images were captured using a Specim IQ hyperspectral camera. The hyperspectral images are in the ENVI format. There are 393 training images, 45 validation images and 75 test images. \n\nIf you use this data, please cite the following paper:\n\nHabili, Nariman, Ernest Kwan, Weihao Li, Christfried Webers, Jeremy Oorloff, Mohammad Ali Armin, and Lars Petersson. "A Hyperspectral and RGB Dataset for Building Façade Segmentation." In Computer Vision–ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part VII, pp. 258-267. Cham: Springer Nature Switzerland, 2023.\n\n@inproceedings{habili2023hyperspectral,\n title={A Hyperspectral and RGB Dataset for Building Fa{\\c{c}}ade Segmentation},\n author={Habili, Nariman and Kwan, Ernest and Li, Weihao and Webers, Christfried and Oorloff, Jeremy and Armin, Mohammad Ali and Petersson, Lars},\n booktitle={Computer Vision--ECCV 2022 Workshops: Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part VII},\n pages={258--267},\n year={2023},\n organization={Springer}\n}\nLineage: The images were captured by a Specim IQ hyperspectral camera.