Ying Fu

Learning Semantic-Robust Change Detection via Semantic-Invariant Self-Distillation

Jiuhe Qu, Yingping Liang, Ying Fu

Change detection aims to identify semantic changes between remote sensing images. However, features from models are easily disturbed by non-semantic variations, such as illumination, shadows, and atmospheric changes, leading to false alarms and limited generalization in real-worl…Read more

Explainable machine learning for 10-year prediction of cognitive impairment in a rural Chinese population

Botang Guo, Shiqi Li, Minyao Li, Yuanshuo Ma, Ying Fu, Yihao Shu, et al.

AquaStereo: Enabling Underwater Stereo Matching via Depth-Conditioned Diffusion and Geometry Self-Distillation

Qizhe Wei, Yingping Liang, Shaodi You, Ying Fu

Learning-based stereo matching models struggle in underwater environments due to scarce in-domain data and the difficulty of extracting discriminative correspondences from degraded imagery. In this work, we present $\textbf{AquaStereo}$, a perception-enhanced framework with a dat…Read more