Search Results for author: Meiqing Wu

Found 7 papers, 1 papers with code

Taylor Series-Inspired Local Structure Fitting Network for Few-shot Point Cloud Semantic Segmentation

no code implementations3 Apr 2025 Changshuo Wang, Shuting He, Xiang Fang, Meiqing Wu, Siew-Kei Lam, Prayag Tiwari

Specifically, inspired by Taylor series, we treat the local structure representation of irregular point clouds as a polynomial fitting problem and propose a novel local structure fitting convolution, called TaylorConv.

Semantic Segmentation

CAP-Context-Aware-Pruning-for-Semantic-Segmentation

no code implementations6 Jan 2021 wei he, Meiqing Wu, Mingfu Liang, Siew-Kei Lam

In this paper, we advocate the importance of contextual information during channel pruning for semantic segmentation networks by presenting a novel Context-aware Pruning framework.

Network Pruning Segmentation +1

CAP: Context-Aware Pruning for Semantic-Segmentation

no code implementations6 Jan 2021 wei he, Meiqing Wu, Mingfu Liang, Siew-Kei Lam

In this paper, we advocate the importance of contextual information during channel pruning for semantic segmentation networks by presenting a novel Context-aware Pruning framework.

Network Pruning Segmentation +1

SSA-CNN: Semantic Self-Attention CNN for Pedestrian Detection

no code implementations25 Feb 2019 Chengju Zhou, Meiqing Wu, Siew-Kei Lam

We propose a method that explores semantic segmentation results as self-attention cues to significantly improve the pedestrian detection performance.

Autonomous Driving Computational Efficiency +3

Situation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model

no code implementations13 Feb 2019 Sirin Haddad, Meiqing Wu, He Wei, Siew Kei Lam

Pedestrian trajectory prediction is essential for collision avoidance in autonomous driving and robot navigation.

Autonomous Driving Collision Avoidance +3

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