Decoupled Data Consistency with Diffusion Purification for Image Restoration

arXiv:2403.06054 · eess.IV, cs.AI, cs.CV, cs.LG, eess.SP · Submitted 2024-03-10 · Read on arXiv

eess.IV, cs.AI, cs.CV, cs.LG, eess.SP

Submitted: 2024-03-10

Updated: 2026-09-02

Code: https://github.com/Morefre/Decoupled-Data-Consistency-with-Diffusion

Terminology

• Consistency — 89× in this paper · explained in 3 episodes
• Diffusion Model — 73× in this paper · explained in 8 episodes
• Diffusion Models — 66× in this paper · explained in 6 episodes
• Inverse Problem — 55× in this paper · explained in 2 episodes
• Fidelity — 47× in this paper · explained in 2 episodes
• Latent Space — 30× in this paper · explained in 7 episodes
• Diffusion Process — 9× in this paper · explained in 2 episodes
• Latent Diffusion Model — 9× in this paper · explained in 2 episodes
• Latent Diffusion Models — 9× in this paper · explained in 2 episodes
• Score Function — 9× in this paper · explained in 4 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Regularization — 7× in this paper · explained in 3 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Decoupling — 4× in this paper · explained in 2 episodes
• Sparsity — 4× in this paper · explained in 4 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Computational overhead — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Latent Diffusion Models (LDMs) — 2× in this paper · explained in 2 episodes
• Posterior Sampling with Latent Diffusion Models — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Adversarial Noise — 1× in this paper · explained in 1 episode
• Bayesian Framework — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Processes — 1× in this paper · explained in 2 episodes
• Diffusive Denoising of Gradient-based Minimization — 1× in this paper
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Learned Perceptual Image Patch Similarity — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Manifold Constrained Gradients — 1× in this paper
• Parsimony — 1× in this paper · explained in 2 episodes
• Peak Signal-to-Noise Ratio — 1× in this paper
• Structural Similarity Index Measure — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
• LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
• A Survey on Diffusion Models for Inverse Problems
• Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing
• DDGM: Solving inverse problems by Diffusive Denoising of Gradient-based Minimization
• Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models
• Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Related papers

• Revisiting Integration of Image and Metadata for DICOM Series Classification: Cross-Attention and Dictionary Learning
• VesselSDF: Distance Field Priors for Vascular Network Reconstruction
• cSVR: Convolutional Slice-to-Volume Reconstruction
• NAIMA: Semantics Aware RGB Guided Depth Super-Resolution
• AneumoBench: A Source-Linked Benchmark for Synthetic-Geometry Transfer in Aneurysm CFD
• RETO: A Rotary-Enhanced Transformer Operator for High-Fidelity Prediction of Automotive Aerodynamics