Awesome-Diffusion-Distillation

This repo collects various distillation methods for the Diffusion model. Welcome to PR the works (papers, repositories) missed by the repo.

Contents

• Papers
  • 2023
  • 2022
  • 2021

Papers

2023

• [ICML]On Architectural Compression of Text-to-Image Diffusion [code]
• [ICML]Consistency Models [code]
• [ICML]Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive [code]
• [ICML]Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion [code]
• [ICME]Accelerating Diffusion Sampling with Classifier-based Feature [code]
• [CVPR]On Distillation of Guided Diffusion [code]
• [NeurIPs]SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds
• [NeurIPs]Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
• [PMLR]Fast Sampling of Diffusion Models via Operator [code]
• [arxiv]BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping
• [arxiv]TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation
• [arxiv]Catch-Up Distillation: You Only Need to Train Once for Accelerating [code]
• [arxiv]Improved Techniques for Training Consistency [code]
• [arxiv]Adversarial Diffusion [code]

2022

• [ICLR]Progressive Distillation for Fast Sampling of Diffusion [code]

2021

• [arxiv]Knowledge Distillation in Iterative Generative Models for Improved Sampling [code]