4 papers
Dual-End Consistency Model
Linwei Dong, Ruoyu Guo, Ge Bai +3
The slow iterative sampling nature remains a major bottleneck for the practical deployment of diffusion and flow-based generative models. While consistency models (CMs) represent a…
TinySR: Pruning Diffusion for Real-World Image Super-Resolution
Linwei Dong, Qingnan Fan, Yuhang Yu +4
Real-world image super-resolution (Real-ISR) focuses on recovering high-quality images from low-resolution inputs that suffer from complex degradations like noise, blur, and compre…
Guiding Distribution Matching Distillation with Gradient-Based Reinforcement Learning
Linwei Dong, Ruoyu Guo, Ge Bai +3
Diffusion distillation, exemplified by Distribution Matching Distillation (DMD), has shown great promise in few-step generation but often sacrifices quality for sampling speed. Whi…
TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-Resolution
Linwei Dong, Qingnan Fan, Yihong Guo +5
Pre-trained text-to-image diffusion models are increasingly applied to real-world image super-resolution (Real-ISR) task. Given the iterative refinement nature of diffusion models,…