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VideoRAE: Taming Video Foundation Models for Generative Modeling via Representation Autoencoders
Video generation models typically rely on 3D-VAEs trained for pixel-level reconstruction, whose latent spaces may underrepresent semantic structure. We introduce VideoRAE, a representation autoencoder that converts features from a frozen video foundation model into compact, reconstruction-capable la
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