Diffusion Models for Image Restoration and Enhancement--A Comprehensive Survey
Image restoration (IR) has been an indispensable and challenging task in the low-level
vision field, which strives to improve the subjective quality of images distorted by various …
vision field, which strives to improve the subjective quality of images distorted by various …
Consistency trajectory models: Learning probability flow ode trajectory of diffusion
Consistency Models (CM)(Song et al., 2023) accelerate score-based diffusion model
sampling at the cost of sample quality but lack a natural way to trade-off quality for speed. To …
sampling at the cost of sample quality but lack a natural way to trade-off quality for speed. To …
Direct diffusion bridge using data consistency for inverse problems
Diffusion model-based inverse problem solvers have shown impressive performance, but
are limited in speed, mostly as they require reverse diffusion sampling starting from noise …
are limited in speed, mostly as they require reverse diffusion sampling starting from noise …
Uncertainty quantification via neural posterior principal components
Uncertainty quantification is crucial for the deployment of image restoration models in safety-
critical domains, like autonomous driving and biological imaging. To date, methods for …
critical domains, like autonomous driving and biological imaging. To date, methods for …
Prompt-tuning latent diffusion models for inverse problems
We propose a new method for solving imaging inverse problems using text-to-image latent
diffusion models as general priors. Existing methods using latent diffusion models for …
diffusion models as general priors. Existing methods using latent diffusion models for …
Wavedm: Wavelet-based diffusion models for image restoration
Latest diffusion-based methods for many image restoration tasks outperform traditional
models, but they encounter the long-time inference problem. To tackle it, this paper …
models, but they encounter the long-time inference problem. To tackle it, this paper …
A survey on diffusion models for inverse problems
Diffusion models have become increasingly popular for generative modeling due to their
ability to generate high-quality samples. This has unlocked exciting new possibilities for …
ability to generate high-quality samples. This has unlocked exciting new possibilities for …
Efficient diffusion models: A comprehensive survey from principles to practices
Z Ma, Y Zhang, G Jia, L Zhao, Y Ma, M Ma… - arXiv preprint arXiv …, 2024 - arxiv.org
As one of the most popular and sought-after generative models in the recent years, diffusion
models have sparked the interests of many researchers and steadily shown excellent …
models have sparked the interests of many researchers and steadily shown excellent …
Osmosis: Rgbd diffusion prior for underwater image restoration
Underwater image restoration is a challenging task because of water effects that increase
dramatically with distance. This is worsened by lack of ground truth data of clean scenes …
dramatically with distance. This is worsened by lack of ground truth data of clean scenes …
Blind audio bandwidth extension: A diffusion-based zero-shot approach
Audio bandwidth extension involves the realistic reconstruction of high-frequency spectra
from bandlimited observations. In cases where the lowpass degradation is unknown, such …
from bandlimited observations. In cases where the lowpass degradation is unknown, such …