What if you could generate stunning AI images in a single step, without compromising quality? Researchers from Westlake University, Chinese Academy of Sciences, and DP Technology present a breakthrough. They've introduced a new framework that simplifies the design of 'shortcut' diffusion models. This framework clarifies how to build more efficient one-step image generators by disentangling their core components. Their model achieves a new state-of-the-art FID50k of 2.85 on ImageNet-256×256 with one-step generation, and 2.53 with two steps. Remarkably, it requires NO pre-training, distillation, or curriculum learning! On the Design of One-step Diffusion via Shortcutting Flow Paths Paper: openreview.net/forum?id=k6q8…  Code: github.com/EDAPINENUT/Explic…    Project: edapinenut.github.io/explici… Our report: mp.weixin.qq.com/s/BptmtBa_O… 📬 #PapersAccepted by Jiqizhixin

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