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20192025
most citedSituation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model

53 citations · 94 across the 5 of their papers we have counts for

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cs.CV2025

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

Changshuo Wang, Shuting He, Xiang Fang +3

Few-shot point cloud semantic segmentation aims to accurately segment "unseen" new categories in point cloud scenes using limited labeled data. However, pretraining-based methods n…

cs.CV2024★ 4 cited

GPSFormer: A Global Perception and Local Structure Fitting-based Transformer for Point Cloud Understanding

Changshuo Wang, Meiqing Wu, Siew-Kei Lam +5

Despite the significant advancements in pre-training methods for point cloud understanding, directly capturing intricate shape information from irregular point clouds without relia…

cs.CV2020★ 2 cited

IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report

Qi She, Fan Feng, Qi Liu +33

This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top finalists (out of over~…

cs.CV2019★ 53 cited

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

Sirin Haddad, Meiqing Wu, He Wei +1

Pedestrian trajectory prediction is essential for collision avoidance in autonomous driving and robot navigation. However, predicting a pedestrian's trajectory in crowded environme…

cs.CV2019★ 35 cited

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

Chengju Zhou, Meiqing Wu, Siew-Kei Lam

Pedestrian detection plays an important role in many applications such as autonomous driving. We propose a method that explores semantic segmentation results as self-attention cues…