NeuS-E is a post-generation refinement method that uses neuro-symbolic analysis of a formal video representation to detect and correct semantic and temporal inconsistencies in text-to-video outputs, improving prompt alignment by nearly 40%.
In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
2 Pith papers cite this work. Polarity classification is still indexing.
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