Solving AI video picture quality and style control problems
When using Video Starter Kit to generate video, picture quality problems can stem from three key areas: vague input commands, improper model parameters, or insufficient data processing. Below is a step-by-step solution:
- Precision Input Design: Adopt the structure of "[Subject] + [Action] + [Scene] + [Style Adjective]" in the text description, e.g. "A dog in a space suit walking on the moon, cyberpunk style, 8K resolution". For image input, it is recommended to use a clear base image of 512×512 pixels or more.
- parameter tuning: Adjust "CFG Scale" (recommended 7-10) in the generation interface to control the creative freedom, and set "Steps" (20-30) to affect the rendering accuracy. The embedded conch video model in the toolkit supports locking the screen style by seed value.
- spectroscopic processing: Complex scenes are recommended to be broken down into multiple clips of 10 seconds or less to be generated individually and then composited with the built-in editing tools. This is much easier to maintain consistent quality than generating a long video all at once!
- post-processing amendment: Use the "Frame Repair" function of the browser editor to locally regenerate the flickering frames; and use the "Color Correction" module to unify the overall color tone.
Advanced techniques include building a style reference gallery (uploading 3-5 images of the same style as a generating reference), and a combination of these methods can dramatically improve image consistency.
This answer comes from the articleAI Video Starter Kit: Full-flow creation and editing of AI videos in the browserThe
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