Jimeng Image-to-Video Prompt Refiner

Problem

Turning a static reference image into video often fails not because the scene is missing, but because the prompt repeats what the reference image already shows—characters, clothing, props, and background—so the model lacks a clear next state. In image-to-video modes such as single-image, first-last-frame, multi-frame, and multimodal reference, vague wording like “beautiful scene” or “push in” can lead to random deformation, subject drift, and style jumps when motion agents, static constraints, pacing, and duration are missing.

How It Works

The skill turns image-to-video prompting into an incremental description workflow. The core rule is describe only what changes and moves: identify the sub-mode, name which elements move, explicitly lock down elements that must stay still, then add camera logic, duration, and style consistency. It pushes for concrete motion language, such as “hair lifts in a light breeze” instead of “wind,” and camera descriptions such as “the camera slowly pushes forward and gradually focuses on the face” rather than only push-in. For multi-frame tasks, it focuses on causal transitions, elapsed time, and narrative continuity instead of re-describing every frame.

Boundaries

Use it when converting reference images, first/last frames, sequence frames, or mixed media into video prompts; it is not meant for pure text-to-video or image-to-image editing. Multi-frame stories generally accept a limited image range, while multimodal reference modes have limits on images, videos, and audio. Style drift can still occur, so include constraints like “keep the reference image’s style and color tone consistent.”