most citedGraph-Driven Multimodal Feature Learning Framework for Apparent Personality Assessment

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

GAME: Learning Multimodal Interactions via Graph Structures for Personality Trait Estimation

Kangsheng Wang, Yuhang Li, Chengwei Ye +5

Apparent personality analysis from short videos poses significant chal-lenges due to the complex interplay of visual, auditory, and textual cues. In this paper, we propose GAME, a…

cs.CV20252 cited

Graph-Driven Multimodal Feature Learning Framework for Apparent Personality Assessment

Kangsheng Wang, Chengwei Ye, Huanzhen Zhang +2

Predicting personality traits automatically has become a challenging problem in computer vision. This paper introduces an innovative multimodal feature learning framework for perso…

eess.SP2025

Non-contact Vital Signs Detection in Dynamic Environments

Shuai Sun, Chong-Xi Liang, Chengwei Ye +2

Accurate phase demodulation is critical for vital sign detection using millimeter-wave radar. However, in complex environments, time-varying DC offsets and phase imbalances can sev…

cs.CV2025

GaMNet: A Hybrid Network with Gabor Fusion and NMamba for Efficient 3D Glioma Segmentation

Chengwei Ye, Huanzhen Zhang, Yufei Lin +3

Gliomas are aggressive brain tumors that pose serious health risks. Deep learning aids in lesion segmentation, but CNN and Transformer-based models often lack context modeling or d…

cs.CV20251 cited

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction

Xuyin Qi, Zeyu Zhang, Huazhan Zheng +19

Bone density prediction via CT scans to estimate T-scores is crucial, providing a more precise assessment of bone health compared to traditional methods like X-ray bone density tes…