# MSR-Net: Multi-Scale Relighting Network for One-to-One Relighting

arXiv: https://arxiv.org/abs/2107.06125 · HTML: https://mlsanity.com/paper/2107.06125/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 17 references that are in the map.
- First posted on arXiv 13 Jul 2021.

## Builds on (most cited first, 12 of 12)

- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Understanding Deep Image Representations by Inverting Them](https://mlsanity.com/paper/1412.0035/) (2014)
- [Scale-recurrent Network for Deep Image Deblurring](https://mlsanity.com/paper/1802.01770/) (2018)
- [GridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing](https://mlsanity.com/paper/1908.03245/) (2019)
- [Deep Stacked Hierarchical Multi-patch Network for Image Deblurring](https://mlsanity.com/paper/1904.03468/) (2019)
- [SfSNet: Learning Shape, Reflectance and Illuminance of Faces in the Wild](https://mlsanity.com/paper/1712.01261/) (2017)
- [Image Demoireing with Learnable Bandpass Filters](https://mlsanity.com/paper/2004.00406/) (2020)
- [VIDIT: Virtual Image Dataset for Illumination Transfer](https://mlsanity.com/paper/2005.05460/) (2020)
- [Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing](https://mlsanity.com/paper/2005.05999/) (2020)
- [Deep Relighting Networks for Image Light Source Manipulation](https://mlsanity.com/paper/2008.08298/) (2020)
- [2D Image Relighting with Image-to-Image Translation](https://mlsanity.com/paper/2006.07816/) (2020)

## Built on by (most cited first, 3 of 3)

- [SIMBAR: Single Image-Based Scene Relighting For Effective Data Augmentation For Automated Driving Vision Tasks](https://mlsanity.com/paper/2204.00644/) (2022)
- [Lasagna: Layered Score Distillation for Disentangled Object Relighting](https://mlsanity.com/paper/2312.00833/) (2023)
- [SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition](https://mlsanity.com/paper/2110.12914/) (2021)

## Abstract (arXiv)

Deep image relighting allows photo enhancement by illumination-specific retouching without human effort and so it is getting much interest lately. Most of the existing popular methods available for relighting are run-time intensive and memory inefficient. Keeping these issues in mind, we propose the use of Stacked Deep Multi-Scale Hierarchical Network, which aggregates features from each image at different scales. Our solution is differentiable and robust for translating image illumination setting from input image to target image. Additionally, we have also shown that using a multi-step training approach to this problem with two different loss functions can significantly boost performance and can achieve a high quality reconstruction of a relighted image.