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LIF-VSR:一种用于视频超分辨率的轻量级框架,具有隐式对齐和注意力融合
Songyi Zhang1,2,3, Hailin Zhang1, Xiaolin Wang2
1School of Telecommunications Engineering, Xidian University, Xi'an 710071, China.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
我们开发了LIF-VSR,这是一种轻量级的视频超分辨率 (VSR) 框架,可以有效地提高视频质量. 这种近乎实时的解决方案使用经济的时间传播和新的融合策略,以实现高性能,最小的计算成本.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 视频处理 视频处理
背景情况:
- 视频超分辨率 (VSR) 技术提高了视频质量,但在计算上往往很昂贵.
- 由于高资源需求,现有方法面临现实应用方面的挑战.
研究的目的:
- 介绍LIF-VSR,这是一个轻量级和高效的框架,用于近乎实时的视频超分辨率.
- 解决当前最先进的VSR方法的计算成本限制.
主要方法:
- 采用单向的反复架构,通过紧的跨内存单元实现经济的时间传播.
- 使用可变形卷积模块来实现隐式特征对齐,使用稀疏注意力融合模块来实现高效的相邻信息聚合,避免3D卷积和光流.
- 实施交叉注意力机制,以成本效益高的时间特征校准.
主要成果:
- 在公共基准上,LIF-VSR只用3.06万个参数实现了具有竞争力的结果.
- 与现有的VSR方法相比,显示了显著较低的计算足迹.
- 在Vid4上达到27.65dB,在SPMC的基准标准上达到31.61dB.
结论:
- LIF-VSR为实时视频超分辨率提供了一种高效有效的解决方案.
- 该框架的轻量级设计和新的模块使高质量的视频增强可用于实际应用.
- 展示了以效率为首的设计在推进VSR技术方面的潜力.
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