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FastSHADE: 移动端实时图像去噪

type: concept tags: [mobile, image-processing, denoising, gpu, photography, real-time] related: [[on-device-inference-memory-pressure]], , sources: - http://arxiv.org/abs/2604.10275v1 created: 2026-04-14

核心问题

Real-time image denoising is essential for modern mobile photography but remains challenging due to the strict latency and power constraints of edge devices. This paper presents FastSHADE (Fast Self-augmented Hierarchical Asymmetric Denoising), a lightweight U-Net-style network tailored for real-time, high-fidelity restoration on mobile GPUs. Our method features a multi-stage architecture incorporating a novel Asymmetric Frequency Denoising Block (AFDB) that decouples spatial structure extraction from high-frequency noise suppression to maximize efficiency, and a Spatially Gated Upsampler (SGU

论文信息

  • 标题: FastSHADE: Fast Self-augmented Hierarchical Asymmetric Denoising for Efficient inference on mobile devices
  • 作者: Nikolay Falaleev
  • 来源: arXiv

方法/架构

详细方法论待补充。参考原始论文获取完整技术细节。

为什么重要

作为手机端 AIOS 生态的一部分，FastSHADE：移动端实时图像去噪 对推动端侧 AI 落地具有重要意义。

关联

  • [[clawmobile-agentic]] — Agent 系统架构
  • [[kv-cache-quantization-ondevice]] — 内存优化