Mechanisms for Realizing Visual Coherence Technology
Reciprocal Attention Value Mixing (RAVM) technology is Story2Board's core algorithm for ensuring smooth scene transitions. This technology intelligently maintains the narrative rhythm of a scene by deeply analyzing the correlation of visual elements in the preceding and following scenes.
Key points of technical realization:
- Modeling spatial and temporal associations between images to identify common visual elements
- Calculate the importance weight of each visual element using the attention mechanism
- Balancing the visual characteristics of old and new scenes through specially designed fusion algorithms
In the actual test, compared with the direct use of the traditional Vincennes model, the RAVM technology can improve the scene coherence score by 2-3 times, which makes the generated series of pictures have an obvious sense of movie and support more complex narrative expression.
This answer comes from the articleStory2Board: generating coherent split-screen scripts from natural language storiesThe
May not be reproduced without permission:AI productivity tools " Story2Board's Mutual Attention Value Blending technology enables natural transitions between scenes.
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