Seventy3

Seventy3: 用NotebookLM将论文生成播客，让大家跟着AI一起进步。

今天的主题是：

DiffuEraser: A Diffusion Model for Video Inpainting

Summary

DiffuEraser is a novel video inpainting model leveraging stable diffusion to address limitations in existing methods. Current video inpainting techniques often struggle with blurring and temporal inconsistencies, especially with large masked areas. DiffuEraser enhances detail and coherence by incorporating prior information to guide the diffusion process and suppress unwanted artifacts. To improve temporal consistency across extended video sequences, it expands the temporal receptive fields and uses the Video Diffusion Model's smoothing properties. The model decomposes video inpainting into known pixel propagation, unknown pixel generation, and temporal consistency, offering targeted solutions for each. Ultimately, DiffuEraser outperforms existing methods by producing more complete and temporally consistent results.

DiffuEraser 是一种新颖的视频修复模型，利用稳定扩散技术来解决现有方法的局限性。当前的视频修复技术在处理大面积遮挡时，常常面临模糊和时间一致性差的问题。DiffuEraser 通过引入先验信息来引导扩散过程，有效增强细节和整体连贯性，同时抑制不必要的伪影。为了提高长视频序列的时间一致性，模型扩展了时间感受野，并利用 Video Diffusion Model 的平滑特性。DiffuEraser 将视频修复任务分解为已知像素传播、未知像素生成和时间一致性维护，并针对每个环节提供专门的解决方案。实验结果表明，该方法相比现有技术能够生成更完整且时间一致性更高的视频内容。

原文链接：https://arxiv.org/abs/2501.10018