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 …
Diff-retinex: Rethinking low-light image enhancement with a generative diffusion model
In this paper, we rethink the low-light image enhancement task and propose a physically
explainable and generative diffusion model for low-light image enhancement, termed as Diff …
explainable and generative diffusion model for low-light image enhancement, termed as Diff …
KGSR: A kernel guided network for real-world blind super-resolution
In recent years, deep learning-based methods have emerged as dominant players in the
field of super-resolution (SR), owing to their exceptional reconstruction performance. The …
field of super-resolution (SR), owing to their exceptional reconstruction performance. The …
ACDMSR: Accelerated conditional diffusion models for single image super-resolution
Diffusion models have gained significant popularity for image-to-image translation tasks.
Previous efforts applying diffusion models to image super-resolution have demonstrated that …
Previous efforts applying diffusion models to image super-resolution have demonstrated that …
Diffusion models, image super-resolution and everything: A survey
Diffusion Models (DMs) represent a significant advancement in image Super-Resolution
(SR), aligning technical image quality more closely with human preferences and expanding …
(SR), aligning technical image quality more closely with human preferences and expanding …
Hyperspectral and panchromatic images fusion based on the dual conditional diffusion models
The fusion between the low-resolution hyperspectral image (LRHSI) and the panchromatic
(PAN) image could obtain the high-resolution hyperspectral image (HRHSI). Recently, deep …
(PAN) image could obtain the high-resolution hyperspectral image (HRHSI). Recently, deep …
Learning from multi-perception features for real-word image super-resolution
Actual image super-resolution is an extremely challenging task due to complex
degradations existing in the image. To solve this problem, two dominant methodologies …
degradations existing in the image. To solve this problem, two dominant methodologies …
GRAN: ghost residual attention network for single image super resolution
Recently, many works have designed wider and deeper networks to achieve higher image
super-resolution performance. Despite their outstanding performance, they still suffer from …
super-resolution performance. Despite their outstanding performance, they still suffer from …
[HTML][HTML] SaltGAN: A feature-infused and loss-controlled generative adversarial network with preserved checkpoints for evolving histopathology images
ON Oyelade, H Wang, SA Adewuyi - Biomedical Signal Processing and …, 2024 - Elsevier
The use of natural phenomena as inspiration to address real-life problems has become an
increasingly popular research approach. In the medical domain, generative adversarial …
increasingly popular research approach. In the medical domain, generative adversarial …
Cross-view Masked Diffusion Transformers for Person Image Synthesis
TX Pham, Z Kang, CD Yoo - arXiv preprint arXiv:2402.01516, 2024 - arxiv.org
We present X-MDPT (Cross-view Masked Diffusion Prediction Transformers), a novel
diffusion model designed for pose-guided human image generation. X-MDPT distinguishes …
diffusion model designed for pose-guided human image generation. X-MDPT distinguishes …