Model Already Knows the Best Noise: Bayesian Active Noise Selection via Attention in Video Diffusion Model

Researchers propose ANSE, a new framework that improves video generation quality in diffusion models by intelligently selecting initial noise seeds based on the model's internal attention patterns. The method uses Bayesian uncertainty quantification to identify high-quality seeds that produce better video quality and temporal coherence with minimal computational overhead.