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English(EN) Keyframe-Centric State-Space Modeling for Burst Image Super-Resolution

BurstMamba架构通过高效帧处理优化图像超分辨率

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了一种新颖的突发图像超分辨率（BISR）架构BurstMamba。该方法通过将处理能力集中于重建高分辨率关键帧，同时利用轻量级流从其他帧提取亚像素信息来优化计算。关键创新包括用于高效跨帧消息传递的Gather-Aggregate-Scatter（GAS）机制，以及用于优先处理高频区域的小波条件状态更新。BurstMamba在多个基准数据集上展示了最先进的性能，消融实验证实了其计算分离和特征提取技术的有效性。 AI

影响 引入了一种新颖的图像超分辨率架构，优化了计算效率和性能。

排序理由 该项目是一篇研究论文，详细介绍了一种新的图像超分辨率模型架构。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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

BurstMamba架构通过高效帧处理优化图像超分辨率

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该项目是一篇研究论文，详细介绍了一种新的图像超分辨率模型架构。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Ozan Unal, Steven Marty, Dengxin Dai ·

    面向突发图像超分辨率的关键帧中心状态空间建模

    arXiv:2503.19634v2 Announce Type: replace Abstract: Burst image super-resolution (BISR) reconstructs a high-resolution keyframe by aggregating complementary sub-pixel evidence from a short burst of low-resolution frames. Existing methods often process all burst frames with heavy …

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