High-fidelity latent priors improve efficient high-resolution image generation

UltraDiff transfers guidance from lightly compressed image latents into a model operating in a substantially smaller latent space.

Big Tech
Jingjing Ren · Haitian Zheng · Haoyu Chen · Connelly Barnes · Zhifei Zhang · Yuqian Zhou · +2 more

The Hong Kong University of Science and Technology (Guangzhou) · Adobe Research

Research Digest··2 min read
Ren et al.

The authors trained MixTeacher, a dual-branch Diffusion Transformer that jointly models paired f8 and f32 latents extracted from the same image.

Why this paper

From Adobe Research and The Hong Kong University of Science and Technology (Guangzhou)

In one line

UltraDiff distills a joint f8-f32 diffusion teacher into an f32 student, approaching f8 image quality at f32 speed.

What we could check

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  • ·No dataset link found
  • ✓Compute or model size stated (hardware A100)
  • ·No stated limitations found
  • ✓Reports numbers on named benchmarks

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Research Digest

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