研究人员开发了多频专家网络（MFEN），以应对可见光-红外行人重识别（VI-ReID）的挑战。该网络旨在克服可见光和红外图像之间显著的模态差异，这种差异通常由不同的光照条件引起。MFEN采用混合专家设计，自适应地结合来自不同频带的信息，增强身份相关细节的提取，同时过滤掉光照变化。随机频率增强和频率辅助优化技术进一步支持了该方法，以改进训练和鲁棒的表示学习。 AI
影响 引入了一种新颖的方法来改善跨不同视觉光谱的行人重识别，可能增强监控和安全系统。
排序理由 该集群包含一篇详细介绍计算机视觉任务新方法的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2606.12051v1 Announce Type: new Abstract: Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. We contend that this discrepancy is largely related to differing lighting conditions, incl…
Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. We contend that this discrepancy is largely related to differing lighting conditions, including differences in light wavelength and light …