activity
20232025
most citedWeakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping

64 citations · 115 across the 15 of their papers we have counts for

collaborators
Showing 2023 · cs.CVShow all

7 papers · 2 filters

cs.CV2023★ 10 cited

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★ 29 cited

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…

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…

cs.CV2023★ 64 cited

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…

cs.CV2023

Towards Realizing the Value of Labeled Target Samples: a Two-Stage Approach for Semi-Supervised Domain Adaptation

mengqun Jin, Kai Li, Shuyan Li +2

Semi-Supervised Domain Adaptation (SSDA) is a recently emerging research topic that extends from the widely-investigated Unsupervised Domain Adaptation (UDA) by further having a fe…

cs.CV2023★ 3 cited

Adversarial Alignment for Source Free Object Detection

Qiaosong Chu, Shuyan Li, Guangyi Chen +2

Source-free object detection (SFOD) aims to transfer a detector pre-trained on a label-rich source domain to an unlabeled target domain without seeing source data. While most exist…