Story Generation Quality Improvement Program
The visual storytelling feature relies on image quality and AI semantic understanding for more in-depth content through the following methods:
- Front Image Selection: Select images that are rich in visual cues (e.g., old photos need to retain text around the edges, multi-person scenes need to highlight the subject)
- two-tier verification method: First use "Image Recognition" to get the basic information, then click "Generate Story" and the AI will combine the metadata to generate a story.
- Language parameterization: Adjust the default language to English (the original generated language) in the settings, and then translate back to Chinese to minimize semantic loss.
- Contextual additions: Manually add 1-2 keywords (e.g. "1950s Shanghai") after shooting to guide the story generation direction.
Special note: The generated narrative content is better suited as an inspirational reference, and important scenes are suggested to be cross-checked with historical facts through the "Learn More" link.
This answer comes from the articleChance AI: Image Recognition and Visual Storytelling through AI TechnologyThe
May not be reproduced without permission:AI productivity tools " How to optimize the richness and accuracy of visual stories generated by Chance AI?
