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cs.CV2026

HadBalance: A Plug-and-Play Unified Global Geometric Prior Framework for Generalizable Biomedical Segmentation

Zhuangzhi Gao, Feixiang Zhou, He Zhao +11

Precise biomedical image segmentation is crucial for clinical diagnosis. Geometric cues (e.g., boundary, shape, and topology) can improve structural consistency, yet most are task-…

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.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

CathAction: A Benchmark for Endovascular Intervention Understanding

Baoru Huang, Tuan Vo, Chayun Kongtongvattana +35

Real-time visual feedback from catheterization analysis is crucial for enhancing surgical safety and efficiency during endovascular interventions. However, existing datasets are of…