Abstract
Video inpainting is a crucial task in computer vision and video editing, involving in removing unnecessary objects and restoration of missing or corrupted regions within a video sequence. One approach that has gained prominence in recent years is the combination of local and global refinement techniques. This innovative strategy leverages the strengths of both local and global information to produce high-quality inpainted videos. In the context of video inpainting, local refinement focuses on accurately restoring missing or damaged regions by considering nearby pixels or frames. Encoder-decoder network can be employed to fill in gaps with content that seamlessly blends with the surrounding context. On the other hand, global refinement seeks to ensure temporal consistency and smooth transitions between frames, preventing noticeable artifacts or jittering in the inpainted video. In conclusion, by seamlessly blending local and global inpainting strategies, these methods can effectively remove unwanted elements from videos while preserving both spatial and temporal coherence. This technology finds applications in video editing, restoration of damaged archival footage, and even in the entertainment industry for special effects and scene corrections, ultimately contributing to the improvement of video quality and aesthetics. Keywords: Video Inpainting, Local and Global Refinement, Encoder-Decoder network, Recurrent Flow Completion, mask-guided sparse video Transformer, dual-domain propagation.
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