Controllable Video Object Insertion via Multi-View Priors
Quick summary
arXiv:2604.14556v2 Announce Type: replace-cross Abstract: Video object insertion places a user-specified object in an existing dynamic scene. Existing methods typically condition generation on text or a single reference image. Consequently, object appearance is underconstrained under viewpoint changes, often leading to identity drift, incorrect foreground-background layering, boundary artifacts, and temporal flickering. In this paper, we propose a video object insertion framework that incorporates multi-view object priors to address these limitations. The framework lifts a 2D reference image i
Key takeaways
- arXiv:2604.14556v2 Announce Type: replace-cross Abstract: Video object insertion places a user-specified object in an existing dynamic scene.
- Existing methods typically condition generation on text or a single reference image.
- Consequently, object appearance is underconstrained under viewpoint changes, often leading to identity drift, incorrect foreground-background layering, boundary artifacts, and temporal flickering.
Why it matters
“Controllable Video Object Insertion via Multi-View Priors” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.
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