Conceptual

High-Fidelity Video Object Insertion with Motion Control

Inserting a reference object into an existing video while preserving its fine appearance details and giving the user precise control over its motion. Built on a text-to-video diffusion model, the approach injects global identity with an ID extractor, controls coarse motion with a box sequence, and adds a pixel warper that warps reference-image pixel details along user-specified key-point trajectories and fuses them into the diffusion U-Net, trained on a mix of videos and static images. Supports downstream tasks like video face swapping, virtual try-on, and multi-region editing without task-specific fine-tuning.