activity
20242026
collaborators

8 papers

cs.CV2026

PARAGraph: Pathology-Anatomy-Aware Hierarchical Graph for Diabetic Retinopathy Grading

Ziyang Zhang, Yuankai Huo, Yalin Zheng +1

Diabetic retinopathy (DR) remains a leading cause of vision loss among working-age adults worldwide, making reliable severity grading clinically important. Despite strong performan…

cs.RO2026

Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution

Hanyi Zhang, Khang Nguyen, Charith Munasinghe +10

Robust robotic grasping remains a fundamental challenge for complex real-world applications. Recent advances in large-scale models demonstrate promising capabilities for reasoning…

cs.CV2026

Disentangled Fine-Grained Prototype Learning for Incomplete Image-Tabular Classification

Feixiang Zhou, Jianyang Xie, Zhuangzhi Gao +10

The missing-modality problem poses a significant challenge in image-tabular multimodal learning across a wide range of multimedia applications, including product understanding, rec…

cs.AI2025

RetiBridge: Bridging Quantitative Retinal Biomarkers and Qualitative Diagnosis with a Knowledge-Guided Multimodal Large Language Model

Zhuangzhi Gao, Hongyi Qin, He Zhao +10

Retinal biomarkers captured by color fundus photography and optical coherence tomography provide clinically valuable evidence for both ocular and systemic diseases. Multimodal larg…

cs.CV2025

GLCP: Global-to-Local Connectivity Preservation for Tubular Structure Segmentation

Feixiang Zhou, Zhuangzhi Gao, He Zhao +5

Accurate segmentation of tubular structures, such as vascular networks, plays a critical role in various medical domains. A remaining significant challenge in this task is structur…

cs.CV2025

Are Spatial-Temporal Graph Convolution Networks for Human Action Recognition Over-Parameterized?

Jianyang Xie, Yitian Zhao, Yanda Meng +3

Spatial-temporal graph convolutional networks (ST-GCNs) showcase impressive performance in skeleton-based human action recognition (HAR). However, despite the development of numero…

cs.CV2025

Incomplete Modality Disentangled Representation for Ophthalmic Disease Grading and Diagnosis

Chengzhi Liu, Zile Huang, Zhe Chen +6

Ophthalmologists typically require multimodal data sources to improve diagnostic accuracy in clinical decisions. However, due to medical device shortages, low-quality data and data…

cs.CV2024

CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting

Qinkai Yu, Jianyang Xie, Anh Nguyen +6

Diabetic retinopathy (DR) is a complication of diabetes and usually takes decades to reach sight-threatening levels. Accurate and robust detection of DR severity is critical for th…