# Hierarchical Regression Network for Spectral Reconstruction from RGB Images

arXiv: https://arxiv.org/abs/2005.04703 · HTML: https://mlsanity.com/paper/2005.04703/

## Key facts

- Cited by 29 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2020.

## Built on by (most cited first, 29 of 29)

- [MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction](https://mlsanity.com/paper/2204.07908/) (2022)
- [NTIRE 2021 Depth Guided Image Relighting Challenge](https://mlsanity.com/paper/2104.13365/) (2021)
- [A survey on computational spectral reconstruction methods from RGB to hyperspectral imaging](https://mlsanity.com/paper/2106.15944/) (2021)
- [Hyperspectral Image Reconstruction via Combinatorial Embedding of Cross-Channel Spatio-Spectral Clues](https://mlsanity.com/paper/2312.11119/) (2023)
- [Deep Amended Gradient Descent for Efficient Spectral Reconstruction from Single RGB Images](https://mlsanity.com/paper/2108.05547/) (2021)
- [Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders](https://mlsanity.com/paper/2204.02084/) (2022)
- [Reciprocal Attention Mixing Transformer for Lightweight Image Restoration](https://mlsanity.com/paper/2305.11474/) (2023)
- [Limitations of Data-Driven Spectral Reconstruction -- An Optics-Aware Analysis](https://mlsanity.com/paper/2401.03835/) (2024)
- [GMSR:Gradient-Guided Mamba for Spectral Reconstruction from RGB Images](https://mlsanity.com/paper/2405.07777/) (2024)
- [Physically Inspired Dense Fusion Networks for Relighting](https://mlsanity.com/paper/2105.02209/) (2021)
- [Continuous Spectral Reconstruction from RGB Images via Implicit Neural Representation](https://mlsanity.com/paper/2112.13003/) (2021)
- [HPRN: Holistic Prior-embedded Relation Network for Spectral Super-Resolution](https://mlsanity.com/paper/2112.14608/) (2021)
- [Depth Estimation from a Single Optical Encoded Image using a Learned Colored-Coded Aperture](https://mlsanity.com/paper/2309.08033/) (2023)
- [Toward Accurate and Reliable Iris Segmentation Using Uncertainty Learning](https://mlsanity.com/paper/2110.10334/) (2021)
- [Learning to Recover Spectral Reflectance from RGB Images](https://mlsanity.com/paper/2304.02162/) (2023)
- [Comparative Analysis of Hyperspectral Image Reconstruction Using Deep Learning for Agricultural and Biological Applications](https://mlsanity.com/paper/2405.13331/) (2024)
- [Inter and Intra Prior Learning-based Hyperspectral Image Reconstruction Using Snapshot SWIR Metasurface](https://mlsanity.com/paper/2407.07503/) (2024)
- [HYDRA: HYbrid knowledge Distillation and spectral Reconstruction Algorithm for high channel hyperspectral camera applications](https://mlsanity.com/paper/2510.16664/) (2025)
- [M3SR: Multi-Scale Multi-Perceptual Mamba for Efficient Spectral Reconstruction](https://mlsanity.com/paper/2601.08293/) (2026)
- [Learning Exhaustive Correlation for Spectral Super-Resolution: Where Spatial-Spectral Attention Meets Linear Dependence](https://mlsanity.com/paper/2312.12833/) (2023)
- [Hyperspectral Image Reconstruction for Predicting Chick Embryo Mortality Towards Advancing Egg and Hatchery Industry](https://mlsanity.com/paper/2405.13843/) (2024)
- [Unleashing Correlation and Continuity for Hyperspectral Reconstruction from RGB Images](https://mlsanity.com/paper/2501.01481/) (2025)
- [From Image- to Pixel-level: Label-efficient Hyperspectral Image Reconstruction](https://mlsanity.com/paper/2503.06852/) (2025)
- [NukesFormers: Unpaired Hyperspectral Image Generation with Non-Uniform Domain Alignment](https://mlsanity.com/paper/2503.07004/) (2025)
- [Modulate and Reconstruct: Learning Hyperspectral Imaging from Misaligned Smartphone Views](https://mlsanity.com/paper/2507.01835/) (2025)
- [A Deep Unfolding Framework for Diffractive Snapshot Spectral Imaging](https://mlsanity.com/paper/2507.04622/) (2025)
- [MCGA: Mixture of Codebooks Hyperspectral Reconstruction via Grayscale-Aware Attention](https://mlsanity.com/paper/2507.09885/) (2025)
- [Uncertainty-Aware Multimodal Fusion for Oral Lesion Classification](https://mlsanity.com/paper/2511.12268/) (2025)
- [Aperture-aware Dispersion 5-D Light-field Imaging Spectrometer](https://mlsanity.com/paper/2607.04635/) (2026)

## Abstract (arXiv)

Capturing visual image with a hyperspectral camera has been successfully applied to many areas due to its narrow-band imaging technology. Hyperspectral reconstruction from RGB images denotes a reverse process of hyperspectral imaging by discovering an inverse response function. Current works mainly map RGB images directly to corresponding spectrum but do not consider context information explicitly. Moreover, the use of encoder-decoder pair in current algorithms leads to loss of information. To address these problems, we propose a 4-level Hierarchical Regression Network (HRNet) with PixelShuffle layer as inter-level interaction. Furthermore, we adopt a residual dense block to remove artifacts of real world RGB images and a residual global block to build attention mechanism for enlarging perceptive field. We evaluate proposed HRNet with other architectures and techniques by participating in NTIRE 2020 Challenge on Spectral Reconstruction from RGB Images. The HRNet is the winning method of track 2 - real world images and ranks 3rd on track 1 - clean images. Please visit the project web page https://github.com/zhaoyuzhi/Hierarchical-Regression-Network-for-Spectral-Reconstruction-from-RGB-Images to try our codes and pre-trained models.