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Dense prediction can achieve superior accuracy and speed by directly utilizing the patch organization of pretrained text-to-image models, bypassing the need for RGB output generation.
Removing inter-token interactions in diffusion models surprisingly boosts performance, revealing that data augmentation is the real driver behind improvements from SRA to Self-Flow.
