64 citations · 71 across the 6 of their papers we have counts for
6 papers
A Survey of Camouflaged Object Detection and Beyond
Fengyang Xiao, Sujie Hu, Yuqi Shen +6
Camouflaged Object Detection (COD) refers to the task of identifying and segmenting objects that blend seamlessly into their surroundings, posing a significant challenge for comput…
Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models
Longxiang Tang, Zhuotao Tian, Kai Li +5
This study addresses the Domain-Class Incremental Learning problem, a realistic but challenging continual learning scenario where both the domain distribution and target classes va…
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…
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…
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…
Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping
Chunming He, Kai Li, Yachao Zhang +5
Weakly-Supervised Concealed Object Segmentation (WSCOS) aims to segment objects well blended with surrounding environments using sparsely-annotated data for model training. It rema…