Layer-Aware Video Composition via Split-then-Merge

The paper introduces Split-then-Merge (StM), a new framework for generative video composition that improves control and tackles data scarcity. StM divides a large set of unlabeled videos into dynamic foreground and background layers, then self‑composes them to learn how subjects interact with varied scenes. The method employs a transformation‑aware training pipeline with multi‑layer fusion, augmentation, and an identity‑preservation loss, achieving superior performance over state‑of‑the‑art methods in both quantitative and qualitative evaluations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

• diffusion
• multimodal
• benchmarks