# A Hyperspectral and RGB Dataset for Building Facade Segmentation

Source: [A Hyperspectral and RGB Dataset for Building Facade Segmentation](<https://www.sota2.com/research/paper/68fa6e1f1e209131cea3df04>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:19:28.729Z

Authors: Nariman Habili, Ernest Kwan, Weihao Li, Christfried Webers, Jeremy Oorloff, Mohammad Ali Armin, Lars Petersson

Published: 2022-12-06T04:38:44.000Z

## Abstract

Hyperspectral Imaging (HSI) provides detailed spectral information and has been utilised in many real-world applications. This work introduces an HSI dataset of building facades in a light industry environment with the aim of classifying different building materials in a scene. The dataset is called the Light Industrial Building HSI (LIB-HSI) dataset. This dataset consists of nine categories and 44 classes. In this study, we investigated deep learning based semantic segmentation algorithms on RGB and hyperspectral images to classify various building materials, such as timber, brick and concrete.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2212.02749>)

[PDF](<https://arxiv.org/pdf/2212.02749.pdf>)