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DeforM boosts video generation realism by directing attention to physics-critical regions, outperforming traditional models in both quality and consistency.
By intelligently pruning attention heads based on their spatial or temporal roles and adaptively routing denoising steps through the network, PARE achieves significant computational savings in video generation without sacrificing quality.
