English(EN) FADPNet: Frequency-Aware Dual-Path Network for Face Super-Resolution

新的FADPNet架构通过双路径处理增强面部超分辨率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-21 04:00

研究人员开发了FADPNet，这是一种新颖的面部超分辨率（FSR）双路径网络，可有效处理低频和高频面部特征。该网络利用基于Mamba的分支处理颜色和纹理等低频分量，以及基于CNN的分支来优化轮廓等高频细节。与现有方法相比，这种方法旨在优化资源分配并提高FSR的质量和效率。 AI

影响为面部超分辨率引入了一种新颖的架构，有望提高图像增强任务的效率和质量。

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arXiv cs.CV TIER_1 English(EN) · Siyu Xu, Wenjie Li, Guangwei Gao, Jian Yang, Guo-Jun Qi, Chia-Wen Lin · 2026-07-21 04:00

FADPNet：用于人脸超分辨率的频率感知双路径网络

arXiv:2506.14121v3 Announce Type: replace Abstract: Face super-resolution (FSR) under limited computational budgets remains challenging. Existing methods often treat all facial pixels equally, leading to suboptimal resource allocation and degraded performance. CNNs are sensitive …