Low-Rank Residual Diffusion Models

Junfu Tan; Jiang Yuan

CVPR2026Top-tier venue

Low-Rank Residual Diffusion Models

Junfu Tan, Jiang Yuan

Publisher

2026Year

Abstract

periments on deraining, deblurring, and deshading benchmarks show that LRDM surpasses full-rank diffusion baselines and achieves state-of-the-art performance, validating the advantage of modeling diffusion in a low-rank residual space. Project

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

What it claims
How it compares
Where it falls short

You ask

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

Terminal

Install the CLI

$ lune papers fulltext af189c15-d9a0-437d-ad3a-c0127968b3ba

Builds on31

Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
Denoising Diffusion Implicit ModelsJiaming Song, Chenlin Meng, Stefano ErmonICLR 2021 · 11,743 citations
Restormer: Efficient Transformer for High-Resolution Image RestorationSyed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat et al.CVPR 2022 · 3,348 citations
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential EquationsChenlin Meng, Yutong He, Yang Song, Jiaming Song et al.ICLR 2022 · 2,128 citations

Abstract

Ask about this paper

Your agent reads all of it.

Builds on31

Related papers