# A Hyperspectral and RGB Dataset for Building Facade Segmentation

arXiv: https://arxiv.org/abs/2212.02749 · HTML: https://mlsanity.com/paper/2212.02749/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 23 references that are in the map.
- First posted on arXiv 6 Dec 2022.

## Builds on (most cited first, 8 of 8)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Fully Convolutional Networks for Semantic Segmentation](https://mlsanity.com/paper/1411.4038/) (2014)
- [Squeeze-and-Excitation Networks](https://mlsanity.com/paper/1709.01507/) (2017)
- [HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification](https://mlsanity.com/paper/1902.06701/) (2019)
- [SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image Classification](https://mlsanity.com/paper/2104.00341/) (2021)
- [Hyperspectral Image Segmentation based on Graph Processing over Multilayer Networks](https://mlsanity.com/paper/2111.15018/) (2021)

## Built on by (most cited first, 7 of 7)

- [What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation](https://mlsanity.com/paper/2306.15521/) (2023)
- [SpectralWaste Dataset: Multimodal Data for Waste Sorting Automation](https://mlsanity.com/paper/2403.18033/) (2024)
- [Joint RGB-Spectral Decomposition Model Guided Image Enhancement in Mobile Photography](https://mlsanity.com/paper/2407.17996/) (2024)
- [DACov: A Deeper Analysis of Data Augmentation on the Computed Tomography Segmentation Problem](https://mlsanity.com/paper/2303.05912/) (2023)
- [HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbone](https://mlsanity.com/paper/2605.17286/) (2026)
- [A General Purpose Spectral Foundational Model for Both Proximal and Remote Sensing Spectral Imaging](https://mlsanity.com/paper/2503.01628/) (2025)
- [Computational Spectral Imaging with Unified Encoding Model: A Comparative Study and Beyond](https://mlsanity.com/paper/2312.13310/) (2023)

## Abstract (arXiv)

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.