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Adversarial Diffusion Distillation (SDXL Turbo)

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Adversarial Diffusion Distillation (SDXL Turbo)
Paper summary

Stability AI's ADD trains a student diffusion model that produces high-quality images in just 1-4 sampling steps.

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Key points
01

Score distillation + adversarial loss: Combines score-distillation from a teacher diffusion model with an adversarial loss to maintain image fidelity in the low-step regime.

02

1-4 step generation: Produces usable images in a single step and SoTA-quality images in four, compared to 25-50 steps for typical SDXL sampling.

03

Matches multi-step SoTA: Achieves image quality comparable to state-of-the-art diffusion baselines at four steps, dramatically cutting inference cost.

04

Real-time generation: Enables SDXL-quality images at real-time frame rates on consumer GPUs, unlocking interactive creative tooling that was previously impractical.

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