most citedHQG-Net: Unpaired Medical Image Enhancement with High-Quality Guidance

5 citations · 5 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2023

Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model

Chunming He, Chengyu Fang, Yulun Zhang +6

Illumination degradation image restoration (IDIR) techniques aim to improve the visibility of degraded images and mitigate the adverse effects of deteriorated illumination. Among t…

cs.CV2023

Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects

Chunming He, Kai Li, Yachao Zhang +5

Camouflaged object detection (COD) is the challenging task of identifying camouflaged objects visually blended into surroundings. Albeit achieving remarkable success, existing COD…

cs.CV2023

Consistency Regularization for Generalizable Source-free Domain Adaptation

Longxiang Tang, Kai Li, Chunming He +2

Source-free domain adaptation (SFDA) aims to adapt a well-trained source model to an unlabelled target domain without accessing the source dataset, making it applicable in a variet…

eess.IV20235 cited

HQG-Net: Unpaired Medical Image Enhancement with High-Quality Guidance

Chunming He, Kai Li, Guoxia Xu +5

Unpaired Medical Image Enhancement (UMIE) aims to transform a low-quality (LQ) medical image into a high-quality (HQ) one without relying on paired images for training. While most…

cs.CV2023

Source-Free Domain Adaptive Fundus Image Segmentation with Class-Balanced Mean Teacher

Longxiang Tang, Kai Li, Chunming He +2

This paper studies source-free domain adaptive fundus image segmentation which aims to adapt a pretrained fundus segmentation model to a target domain using unlabeled images. This…