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Author

Lin Hu

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Open access Oct 2026

Self-supervised 3D point cloud prediction for moving objects based on deep correlation information

This work reformulate point cloud prediction as a unified spatio-temporal correlation learning problem and proposes a novel framework, the Motion-guided Spatio-Temporal Point Cloud Prediction Network (MoCNet), which achieves higher prediction accuracy and better generalization ability.

Kai Gao, Yu-Xiang Zhou, Ping-Ping Dong et al. · 0 citations
Aug 2026

ODE-Net: Occluded traffic sign detection and occlusion percentage estimation via frequency-aware feature fusion

This paper proposes ODE-Net, an advanced YOLOv11-based detection framework with three key contributions, which achieves 94.4% occlusion-prediction accuracy while maintaining a compact size and low computational cost, thereby achieving a superior accuracy-efficiency balance.

Jia-Cai Liao, Le Luo, Lin Hu et al. · 0 citations

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