Accelerating Image Generation with Sub-path Linear Approximation Model

arXiv:2404.13903v1 Announce Type: new
Abstract: Diffusion models have significantly advanced the state of the art in image, audio, and video generation tasks. However, their applications in practical scenarios are hindered by slow inference speed. Drawing inspiration from the approximation strategies utilized in consistency models, we propose the Sub-path Linear Approximation Model (SLAM), which accelerates diffusion models while maintaining high-quality image generation. SLAM treats the PF-ODE trajectory as a series of PF-ODE sub-paths divided by sampled points, and harnesses sub-path linear …

abstract advanced applications approximation art arxiv audio cs.cv diffusion diffusion models however image image generation inference inspiration linear path practical slam speed state state of the art strategies tasks type video video generation