DC-VSR：基于视频扩散先验的时空一致性视频超分辨率 (DC-VSR: Spatially and Temporally Consistent Video Super-Resolution with Video Diffusion Prior)

Video super-resolution (VSR) aims to reconstruct a high-resolution (HR) video from a low-resolution (LR) counterpart. Achieving successful VSR requires producing realistic HR details and ensuring both spatial and temporal consistency. To restore realistic details, diffusion-based VSR approaches have recently been proposed. However, the inherent randomness of diffusion, combined with their tile-based approach, often leads to spatio-temporal inconsistencies. In this paper, we propose DC-VSR, a novel VSR approach to produce spatially and temporally consistent VSR results with realistic textures. To achieve spatial and temporal consistency, DC-VSR adopts a novel Spatial Attention Propagation (SAP) scheme and a Temporal Attention Propagation (TAP) scheme that propagate information across spatio-temporal tiles based on the self-attention mechanism. To enhance high-frequency details, we also introduce Detail-Suppression Self-Attention Guidance (DSSAG), a novel diffusion guidance scheme. Comprehensive experiments demonstrate that DC-VSR achieves spatially and temporally consistent, high-quality VSR results, outperforming previous approaches.

翻译：视频超分辨率（VSR）旨在从低分辨率（LR）视频重建出高分辨率（HR）视频。成功的VSR需要生成逼真的HR细节，并确保空间和时间上的一致性。为了恢复逼真的细节，近期提出了基于扩散模型的VSR方法。然而，扩散过程固有的随机性，结合其基于分块的处理方式，常常导致时空不一致性。本文提出DC-VSR，一种新颖的VSR方法，旨在生成具有逼真纹理且时空一致的VSR结果。为实现时空一致性，DC-VSR采用了一种新颖的空间注意力传播（SAP）方案和时间注意力传播（TAP）方案，它们基于自注意力机制在时空分块间传播信息。为了增强高频细节，我们还引入了细节抑制自注意力引导（DSSAG），一种新颖的扩散引导方案。综合实验表明，DC-VSR能够实现时空一致的高质量VSR结果，性能优于先前方法。