PDD enables fast video/image generation (4-8 steps instead of 50+) with simpler training than current methods, while actually improving output diversity—making it practical for scaling generative models to production.
This paper introduces Parallel Decoding Distillation (PDD), a method to speed up image and video generation from diffusion models by predicting multiple denoising steps at once instead of one at a time.