English(EN) AMIEOD: Adaptive Multi-Experts Image Enhancement for Object Detection in Low-Illumination Scenes

AMIEOD框架增强低光照场景下的目标检测

作者 PulseAugur 编辑部 · [2 个来源] · 2026-05-07 12:06

研究人员开发了AMIEOD，一个旨在增强低照度环境下目标检测能力的新型框架。该系统联合优化图像增强和目标检测任务，利用一个采用多种增强策略的多专家图像增强模块（MEIEM）。该框架还引入了一个检测引导回归损失（DGRL）和一个专家选择模块（ESM），以根据检测性能动态调整增强技术。 AI

影响提高在具有挑战性的低光照条件下的目标检测准确性，可能使自主系统和监控受益。

排序理由这是一篇详细介绍图像处理和目标检测新技术框架的研究论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.CV TIER_1 English(EN) · Xiaochen Huang, Honggang Chen, Weicheng Zhang, Xiaobo Dai, Yongyi Li, Linbo Qing, Xiaohai He · 2026-05-08 04:00

AMIEOD：低照度场景目标检测的自适应多专家图像增强

arXiv:2605.06084v1 Announce Type: new Abstract: In multimedia application scenarios, images captured under low-illumination conditions often lead to lower accuracy in visual perception tasks compared to those taken in well-lit environments. To tackle this challenge, we propose AM…
arXiv cs.CV TIER_1 English(EN) · Xiaohai He · 2026-05-07 12:06

AMIEOD：低照度场景目标检测的自适应多专家图像增强

In multimedia application scenarios, images captured under low-illumination conditions often lead to lower accuracy in visual perception tasks compared to those taken in well-lit environments. To tackle this challenge, we propose AMIEOD, an image enhancement-enabled object detect…