Sparkle: Realizing Lively Instruction-Guided Video Background Replacement via Decoupled Guidance
In recent years, open-source efforts like Senorita-2M have propelled video editing toward natural language instruction. However, current publicly available datasets predominantly focus on local editing or style transfer, which largely preserve the original scene structure and are easier to scale. In contrast, Background Replacement, a task central to creative applications such as film production and advertising, requires synthesizing entirely new, temporally consistent scenes while maintaining accurate foreground-background interactions, making large-scale data generation significantly more challenging. Consequently, this complex task remains largely underexplored due to a scarcity of hig...
| Authors | Ziyun Zeng, Yiqi Lin, Guoqiang Liang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 7 May 2026 |
| Last updated at source | 7 May 2026 |
Connected in the knowledge graph
- stdKonjac/Sparkle-BenchDataset · cited by
- stdKonjac/SparkleDataset · cited by
Models and datasets referencing this paper
- stdKonjac/SparkleDataset
- stdKonjac/Sparkle-BenchDataset
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