Abstract
This paper addresses low-light video super-resolution (LVSR), aiming to restore high-resolution videos from low-light, low-resolution (LR) inputs. Existing LVSR methods often struggle to recover fine details due to limited contrast and insufficient high-frequency information. To overcome these challenges, we present RetinexEVSR, the first event-driven LVSR framework that leverages high-contrast event signals and Retinex-inspired priors to enhance video quality under low-light scenarios. Unlike previous approaches that directly fuse degraded signals, RetinexEVSR introduces a novel bidirectional cross-modal fusion strategy to extract and integrate meaningful cues from noisy event data and degraded RGB frames. Specifically, an illumination-guided event enhancement module is designed to progressively refine event features using illumination maps derived from the Retinex model, thereby suppressing low-light artifacts while preserving high-contrast details. Furthermore, we propose an event-guided reflectance enhancement module that utilizes the enhanced event features to dynamically recover reflectance details via a multi-scale fusion mechanism. Experimental results show that our RetinexEVSR achieves state-of-the-art performance on three datasets. Notably, on the SDSD benchmark, our method can get up to 2.95 dB gain while reducing runtime by 65% compared to prior event-based methods. Code: this https URL.
Abstract (translated)
本文探讨了低光视频超分辨率（LVSR）问题，目标是从低光照、低分辨率的输入中恢复高分辨率视频。现有的LVSR方法往往难以恢复精细细节，因为它们受到对比度有限和高频信息不足的影响。为了解决这些问题，我们提出了RetinexEVSR框架，这是首个基于事件驱动的LVSR框架，该框架利用了高对比度的事件信号和受Retinex启发的先验知识，在低光场景下提升视频质量。与以往直接融合受损信号的方法不同，RetinexEVSR引入了一种新颖的双向跨模态融合策略，用于从噪声事件数据和退化RGB帧中提取并整合有意义的信息。 具体而言，RetinexEVSR设计了一个光照引导的事件增强模块，该模块利用从Retinex模型中得出的光照图逐步精炼事件特征，从而在抑制低光伪影的同时保持高对比度细节。此外，我们还提出了一种基于事件反射率增强的模块，通过多尺度融合机制动态恢复反射率细节，利用了改进后的事件特性。 实验结果显示，在三个数据集上，我们的RetinexEVSR框架取得了最先进的性能表现。特别地，在SDSD基准测试中，与先前基于事件的方法相比，该方法在降低65%运行时间的同时，可以实现最高2.95dB的增益。 代码可在此处获得：[这个链接](https://this-url.com)（注：请将"this https URL"替换为实际的链接地址）。
URL
https://arxiv.org/abs/2601.02206
