Story2Board solves the three major technical bottlenecks of traditional tools through innovative architectural design:
- Potential panel anchoring techniques: Establishing a character feature datum in potential space ensures that subsequent generation is always anchored to that feature set. This is in contrast to normal AI drawing tools that build features from scratch for each generation.
- Dynamic Attention Control: Automatically reinforce the degree of preservation of key character features (e.g., hairstyle/clothing) when generating new frames by adjusting the weight of the attention mechanism of the transformer model.
- Cross-frame feature fusionWhen the scene changes drastically, the RAVM technology creates a feature transfer channel between multiple frames to avoid sudden character changes.
Empirical tests show that under the same cue word condition, Story2Board's character trait retention accuracy is 60-80% higher than generalized models such as Stable Diffusion, which is especially suitable for long narrative creation that requires strict character management.
This answer comes from the articleStory2Board: generating coherent split-screen scripts from natural language storiesThe
May not be reproduced without permission:AI productivity tools " What are the technical advantages of Story2Board over traditional AI drawing tools in terms of maintaining character consistency?
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