Yahong Chen — accepted AI-conference papers

2026

GS-ASM: 2DGS-Supervised Active Stereo Matching

Zhengling Wu, Rongfeng Lu, Quan Chen, Longjian Zeng, Ming Lu, Yaoqi Sun +3

CVPR 2026

Due to the lack of ground truth, existing methods of active stereo matching generally employ fully self-supervised learning to produce precise depth estimates. Although they can achieve promising results, their performance still has a noticeable gap compared with supervised models. To fill this gap,

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2026

Learning Topology-Aware Dynamic Associations for Robust Multi-Person Pose Estimation

Shengnan Hu, Yandong Liu, Jiangnan Liu, Yahong Chen

AAAI 2026technical

Multi-person pose estimation in real-world scenarios remains a challenging task due to frequent occlusions, scale variations, and complex human interactions. Existing methods often rely on fixed keypoint association patterns that fail to capture the dynamic and context-dependent nature of human body

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