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Advancing End-to-End Pixel-Space Generative Modeling via Self-Supervised Pre-Training

Pixel-space generative models are often more difficult to train and generally underperform compared to their latent-space counterparts, leaving a persistent performance and efficiency gap. In this paper, we introduce a novel two-stage training framework that closes this gap for pixel-space diffusion…