English(EN) EvLIR: Learning Illumination Residuals from Ordered Events for Low-Light Image Enhancement

EvLIR框架利用有序事件数据增强低光图像

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-28 14:47

研究人员开发了EvLIR，一个利用事件相机提供的有序事件数据的低光图像增强新框架。与先前将事件数据视为静态的方法不同，EvLIR使用时间事件残差模块（TERM）显式地对短窗口内的亮度变化的时间演变进行建模。这种方法为照明估计和图像恢复生成空间自适应的指导，在多个基准测试中取得了最先进的结果。 AI

影响这项研究引入了一种新的图像增强方法，可以提高各种应用在低光条件下的性能。

排序理由该集群描述了一篇详细介绍新颖技术方法的最新研究论文。

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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Hugging Face Daily Papers TIER_1 English(EN) · 2026-06-28 14:47

EvLIR：从有序事件中学习光照残差以增强低光图像

Low-light image enhancement is severely ill-posed when the input frame contains missing structure, saturated noise, and weak local contrast. Event cameras provide asynchronous brightness-change observations with high temporal resolution, but prior works often treat voxel channels…