Workflow Guide
Image to Video Generator for Product Shots, Posters, and Key Art
Start from a still image and animate it into a short clip while keeping more of the original composition, product framing, or character pose than prompt-only generation usually preserves.
When To Use Image To Video
Use image to video when the frame already matters: a product hero shot, a campaign visual, a comic panel, a 3D render, or a storyboard frame that needs motion added without changing the core composition too aggressively.
How AuraTuner Fits
AuraTuner lets you test Veo, Seedance, and Kling side by side. That makes it easier to decide whether you need simple single-image animation, stricter frame guidance, or a more flexible multimodal reference path.
Source Image Checklist
Use a clean image with clear subject edges, enough background room for camera movement, and no tiny text that must stay perfect. If the product label, lighting, or background is messy, fix the still first with image to image before animating it.
Common Failure Pattern
Most drift comes from asking for too much: large camera moves, body deformation, object transformation, or hidden areas the model must invent. Keep the first prompt conservative when product shape or character identity matters.
Related Pages
Text to Video
Text to video workflow for prompt-led ads and storyboard clips.
Veo 3.1
Veo 3.1 model page for premium short-form image to video clips.
Seedance 2.0
Seedance 2.0 model page for reference-led and multimodal video workflows.
Text vs Image to Video
Workflow comparison for text to video vs image to video.
Image to Video FAQ
These questions reflect common search intent around animating still images, product renders, and campaign artwork.
What images work best for image to video?
Use a clean source image with a clear subject, stable product edges, minimal blur, and enough background space for motion. Avoid screenshots, heavy compression, tiny logos, and crowded frames when fidelity matters.
Why does an image-to-video result drift from the source?
Drift usually happens when the prompt asks for too much subject deformation, the source image has ambiguous edges, or the model invents hidden areas during camera movement. Keep the first test conservative when product shape matters.