The original title is "Image-to-Video Is a Constraint Problem: A Practical Seedance 2.0 Workflow"

Short summary

Image-to-video generation with Seedance 2.0 is best treated as a constraint-management problem rather than a prompt-writing contest. The workflow involves selecting a high-resolution reference image with clean edges and controlled lighting, then requesting motion that stays within the visual information already present in the source. By scoping requests to subtle camera moves and micro-actions instead of complex full-body animation, creators can avoid identity drift, texture flicker, and unstable outputs.

• •Treat image-to-video as constraint management: anchor identity with a strong reference, request motion the source can support, evaluate one variable at a time
• •Choose high-resolution images (768px+ shortest side) with clean alpha edges, controlled lighting, and framing that matches your motion budget
• •Favor subtle moves like slow push-ins, gentle parallax, and micro-actions over vague prompts like 'make it dynamic' that cause identity drift and flicker

Generated with AI, which can make mistakes.