activity
20192025
most citedPALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation

2 citations · 10 across the 10 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2025

AuralSAM2: Enabling SAM2 Hear Through Pyramid Audio-Visual Feature Prompting

Yuyuan Liu, Yuanhong Chen, Chong Wang +6

Segment Anything Model 2 (SAM2) exhibits strong generalisation for promptable segmentation in video clips; however, its integration with the audio modality remains underexplored. E…

cs.CV2023

Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Junde Wu, Wei Ji, Yuanpei Liu +4

The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation tasks and its prompt-b…

cs.CV20221 cited

ExpNet: A unified network for Expert-Level Classification

Junde Wu, Huihui Fang, Yehui Yang +4

Different from the general visual classification, some classification tasks are more challenging as they need the professional categories of the images. In the paper, we call them…

cs.CV2022

An Efficient Person Clustering Algorithm for Open Checkout-free Groceries

Junde Wu, Yu Zhang, Rao Fu +2

Open checkout-free grocery is the grocery store where the customers never have to wait in line to check out. Developing a system like this is not trivial since it faces challenges…

cs.CV2022

Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification

Wenshuo Zhou, Dalu Yang, Binghong Wu +6

Deep learning based medical imaging classification models usually suffer from the domain shift problem, where the classification performance drops when training data and real-world…

cs.CV20202 cited

Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning

Junde Wu, Shuang Yu, Wenting Chen +5

Recently, deep learning has been adopted to the glaucoma classification task with performance comparable to that of human experts. However, a well trained deep learning model deman…