AI RESEARCH
Dynamic Video Generation: Shaping Video Generation Across Time and Space
arXiv CS.CV
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ArXi:2605.21042v1 Announce Type: new Diffusion models have achieved impressive performance in video generation, but their iterative denoising process remains computationally expensive due to the large number of tokens processed at each timestep. Recently, progressive resolution sampling has emerged as a promising acceleration approach by reducing latent resolution in early stages. However, scaling this idea to video generation remains challenging, as the additional temporal dimension