# Multi-Bracket High Dynamic Range Imaging with Event Cameras

arXiv: https://arxiv.org/abs/2203.06622 · HTML: https://mlsanity.com/paper/2203.06622/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 69 references that are in the map.
- First posted on arXiv 13 Mar 2022.

## Builds on (most cited first, 30 of 30)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting](https://mlsanity.com/paper/1506.04214/) (2015)
- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [Deformable ConvNets v2: More Deformable, Better Results](https://mlsanity.com/paper/1811.11168/) (2018)
- [Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement](https://mlsanity.com/paper/2001.06826/) (2020)
- [EDVR: Video Restoration with Enhanced Deformable Convolutional Networks](https://mlsanity.com/paper/1905.02716/) (2019)
- [EnlightenGAN: Deep Light Enhancement without Paired Supervision](https://mlsanity.com/paper/1906.06972/) (2019)
- [High Speed and High Dynamic Range Video with an Event Camera](https://mlsanity.com/paper/1906.07165/) (2019)
- [End-to-End Learning of Representations for Asynchronous Event-Based Data](https://mlsanity.com/paper/1904.08245/) (2019)
- [Events-to-Video: Bringing Modern Computer Vision to Event Cameras](https://mlsanity.com/paper/1904.08298/) (2019)
- [HDR image reconstruction from a single exposure using deep CNNs](https://mlsanity.com/paper/1710.07480/) (2017)
- [Video to Events: Recycling Video Datasets for Event Cameras](https://mlsanity.com/paper/1912.03095/) (2019)
- [Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline](https://mlsanity.com/paper/2004.01179/) (2020)
- [Attention-guided Network for Ghost-free High Dynamic Range Imaging](https://mlsanity.com/paper/1904.10293/) (2019)
- [Deep High Dynamic Range Imaging with Large Foreground Motions](https://mlsanity.com/paper/1711.08937/) (2017)
- [Event-based High Dynamic Range Image and Very High Frame Rate Video Generation using Conditional Generative Adversarial Networks](https://mlsanity.com/paper/1811.08230/) (2018)
- [ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content](https://mlsanity.com/paper/1803.02266/) (2018)
- [HDR-GAN: HDR Image Reconstruction from Multi-Exposed LDR Images with Large Motions](https://mlsanity.com/paper/2007.01628/) (2020)
- [DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs](https://mlsanity.com/paper/1712.07384/) (2017)
- [Single Image HDR Reconstruction Using a CNN with Masked Features and Perceptual Loss](https://mlsanity.com/paper/2005.07335/) (2020)
- [Handheld Mobile Photography in Very Low Light](https://mlsanity.com/paper/1910.11336/) (2019)
- [How to Calibrate Your Event Camera](https://mlsanity.com/paper/2105.12362/) (2021)
- [ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging](https://mlsanity.com/paper/2105.10697/) (2021)
- [Deep Learning for HDR Imaging: State-of-the-Art and Future Trends](https://mlsanity.com/paper/2110.10394/) (2021)
- [NTIRE 2021 Challenge on High Dynamic Range Imaging: Dataset, Methods and Results](https://mlsanity.com/paper/2106.01439/) (2021)
- [An Asynchronous Kalman Filter for Hybrid Event Cameras](https://mlsanity.com/paper/2012.05590/) (2020)
- [Locally Non-rigid Registration for Mobile HDR Photography](https://mlsanity.com/paper/1504.01441/) (2015)
- [Convolutional Sparse Coding for High Dynamic Range Imaging](https://mlsanity.com/paper/1806.04942/) (2018)
- [Real-time Tone Mapping: A State of the Art Report](https://mlsanity.com/paper/2003.03074/) (2020)

## Built on by (most cited first, 30 of 37)

- [Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks](https://mlsanity.com/paper/2302.08890/) (2023)
- [RGB-Event Fusion for Moving Object Detection in Autonomous Driving](https://mlsanity.com/paper/2209.08323/) (2022)
- [HyperE2VID: Improving Event-Based Video Reconstruction via Hypernetworks](https://mlsanity.com/paper/2305.06382/) (2023)
- [Mitigating Motion Blur in Neural Radiance Fields with Events and Frames](https://mlsanity.com/paper/2403.19780/) (2024)
- [Chasing Day and Night: Towards Robust and Efficient All-Day Object Detection Guided by an Event Camera](https://mlsanity.com/paper/2309.09297/) (2023)
- [NTIRE 2025 Challenge on Event-Based Image Deblurring: Methods and Results](https://mlsanity.com/paper/2504.12401/) (2025)
- [Complementing Event Streams and RGB Frames for Hand Mesh Reconstruction](https://mlsanity.com/paper/2403.07346/) (2024)
- [Low-Light Image Enhancement using Event-Based Illumination Estimation](https://mlsanity.com/paper/2504.09379/) (2025)
- [Temporal-Mapping Photography for Event Cameras](https://mlsanity.com/paper/2403.06443/) (2024)
- [An Asynchronous Linear Filter Architecture for Hybrid Event-Frame Cameras](https://mlsanity.com/paper/2309.01159/) (2023)
- [Segment Any Events via Weighted Adaptation of Pivotal Tokens](https://mlsanity.com/paper/2312.16222/) (2023)
- [SEE: See Everything Every Time -- Adaptive Brightness Adjustment for Broad Light Range Images via Events](https://mlsanity.com/paper/2502.21120/) (2025)
- [CrossZoom: Simultaneously Motion Deblurring and Event Super-Resolving](https://mlsanity.com/paper/2309.16949/) (2023)
- [SpikeNVS: Enhancing Novel View Synthesis from Blurry Images via Spike Camera](https://mlsanity.com/paper/2404.06710/) (2024)
- [EvMAPPER: High Altitude Orthomapping with Event Cameras](https://mlsanity.com/paper/2409.18120/) (2024)
- [Seeing Behind Dynamic Occlusions with Event Cameras](https://mlsanity.com/paper/2307.15829/) (2023)
- [Event Camera Demosaicing via Swin Transformer and Pixel-focus Loss](https://mlsanity.com/paper/2404.02731/) (2024)
- [HDR Imaging for Dynamic Scenes with Events](https://mlsanity.com/paper/2404.03210/) (2024)
- [Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging](https://mlsanity.com/paper/2404.11511/) (2024)
- [Event Camera Guided Visual Media Restoration & 3D Reconstruction: A Survey](https://mlsanity.com/paper/2509.09971/) (2025)
- [Segment Any Events with Language](https://mlsanity.com/paper/2601.23159/) (2026)
- [Enabling High-Quality In-the-Wild Imaging from Severely Aberrated Metalens Bursts](https://mlsanity.com/paper/2510.10083/) (2025)
- [EvPlug: Learn a Plug-and-Play Module for Event and Image Fusion](https://mlsanity.com/paper/2312.16933/) (2023)
- [Raw2Event: Converting Raw Frame Camera into Event Camera](https://mlsanity.com/paper/2509.06767/) (2025)
- [Coded-E2LF: Coded Aperture Light Field Imaging from Events](https://mlsanity.com/paper/2602.22620/) (2026)
- [EmambaIR: Efficient Visual State Space Model for Event-guided Image Reconstruction](https://mlsanity.com/paper/2605.08073/) (2026)
- [Event Fusion Photometric Stereo Network](https://mlsanity.com/paper/2303.00308/) (2023)
- [High Dynamic Range Imaging via Visual Attention Modules](https://mlsanity.com/paper/2307.14705/) (2023)
- [OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras](https://mlsanity.com/paper/2408.09424/) (2024)
- [From Events to Enhancement: A Survey on Event-Based Imaging Technologies](https://mlsanity.com/paper/2505.05488/) (2025)

## Abstract (arXiv)

Modern high dynamic range (HDR) imaging pipelines align and fuse multiple low dynamic range (LDR) images captured at different exposure times. While these methods work well in static scenes, dynamic scenes remain a challenge since the LDR images still suffer from saturation and noise. In such scenarios, event cameras would be a valid complement, thanks to their higher temporal resolution and dynamic range. In this paper, we propose the first multi-bracket HDR pipeline combining a standard camera with an event camera. Our results show better overall robustness when using events, with improvements in PSNR by up to 5dB on synthetic data and up to 0.7dB on real-world data. We also introduce a new dataset containing bracketed LDR images with aligned events and HDR ground truth.