# Hyperspectral Image Dataset for Benchmarking on Salient Object Detection

arXiv: https://arxiv.org/abs/1806.11314 · HTML: https://mlsanity.com/paper/1806.11314/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 22 references that are in the map.
- First posted on arXiv 29 Jun 2018.

## Builds on (most cited first, 1 of 1)

- [Saliency Detection by Forward and Backward Cues in Deep-CNNs](https://mlsanity.com/paper/1703.00152/) (2017)

## Built on by (most cited first, 17 of 17)

- [DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object Detection](https://mlsanity.com/paper/2404.00694/) (2024)
- [Neural Spectro-polarimetric Fields](https://mlsanity.com/paper/2306.12562/) (2023)
- [Spectrum-driven Mixed-frequency Network for Hyperspectral Salient Object Detection](https://mlsanity.com/paper/2312.01060/) (2023)
- [Dual-stage Hyperspectral Image Classification Model with Spectral Supertoken](https://mlsanity.com/paper/2407.07307/) (2024)
- [Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset](https://mlsanity.com/paper/2311.17396/) (2023)
- [Spectrum-oriented Point-supervised Saliency Detector for Hyperspectral Images](https://mlsanity.com/paper/2412.18112/) (2024)
- [Learning-Augmented Frequent Directions](https://mlsanity.com/paper/2503.00937/) (2025)
- [HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbone](https://mlsanity.com/paper/2605.17286/) (2026)
- [AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution](https://mlsanity.com/paper/2502.06894/) (2025)
- [Hyperspectral Remote Sensing Images Salient Object Detection: The First Benchmark Dataset and Baseline](https://mlsanity.com/paper/2504.02416/) (2025)
- [HyperCOD: The First Challenging Benchmark and Baseline for Hyperspectral Camouflaged Object Detection](https://mlsanity.com/paper/2601.03736/) (2026)
- [Learning Sparsity and Randomness for Data-driven Low Rank Approximation](https://mlsanity.com/paper/2212.08186/) (2022)
- [Learning the Positions in CountSketch](https://mlsanity.com/paper/2306.06611/) (2023)
- [Signal Recovery Using a Spiked Mixture Model](https://mlsanity.com/paper/2501.01840/) (2025)
- [HSOD-BIT-V2: A New Challenging Benchmarkfor Hyperspectral Salient Object Detection](https://mlsanity.com/paper/2503.13906/) (2025)
- [HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation](https://mlsanity.com/paper/2605.13581/) (2026)
- [Spectral-Spatial Synergistic Guided Network for Hyperspectral Salient Object Detection](https://mlsanity.com/paper/2607.21032/) (2026)

## Abstract (arXiv)

Many works have been done on salient object detection using supervised or unsupervised approaches on colour images. Recently, a few studies demonstrated that efficient salient object detection can also be implemented by using spectral features in visible spectrum of hyperspectral images from natural scenes. However, these models on hyperspectral salient object detection were tested with a very few number of data selected from various online public dataset, which are not specifically created for object detection purposes. Therefore, here, we aim to contribute to the field by releasing a hyperspectral salient object detection dataset with a collection of 60 hyperspectral images with their respective ground-truth binary images and representative rendered colour images (sRGB). We took several aspects in consideration during the data collection such as variation in object size, number of objects, foreground-background contrast, object position on the image, and etc. Then, we prepared ground truth binary images for each hyperspectral data, where salient objects are labelled on the images. Finally, we did performance evaluation using Area Under Curve (AUC) metric on some existing hyperspectral saliency detection models in literature. The dataset is publicly available on our GitHub repository and Hugging Face dataset hub. Repository: https://github.com/nevrez/HS-SOD; (Old original repository https://github.com/gistairc/HS-SOD) Dataset: https://huggingface.co/datasets/gsvrg/HS-SOD.