63 citations · 212 across the 24 of their papers we have counts for
7 papers · 1 filter
Dynamic Hypergraph Convolutional Networks for Skeleton-Based Action Recognition
Jinfeng Wei, Yunxin Wang, Mengli Guo +3
Graph convolutional networks (GCNs) based methods have achieved advanced performance on skeleton-based action recognition task. However, the skeleton graph cannot fully represent t…
SSAGCN: Social Soft Attention Graph Convolution Network for Pedestrian Trajectory Prediction
Pei Lv, Wentong Wang, Yunxin Wang +3
Pedestrian trajectory prediction is an important technique of autonomous driving, which has become a research hot-spot in recent years. Previous methods mainly rely on the position…
Contrastive Proposal Extension with LSTM Network for Weakly Supervised Object Detection
Pei Lv, Suqi Hu, Tianran Hao
Weakly supervised object detection (WSOD) has attracted more and more attention since it only uses image-level labels and can save huge annotation costs. Most of the WSOD methods u…
User-Guided Personalized Image Aesthetic Assessment based on Deep Reinforcement Learning
Pei Lv, Jianqi Fan, Xixi Nie +5
Personalized image aesthetic assessment (PIAA) has recently become a hot topic due to its usefulness in a wide variety of applications such as photography, film and television, e-c…
Emotional Contagion-Aware Deep Reinforcement Learning for Antagonistic Crowd Simulation
Pei Lv, Qingqing Yu, Boya Xu +3
The antagonistic behavior in the crowd usually exacerbates the seriousness of the situation in sudden riots, where the antagonistic emotional contagion and behavioral decision maki…
Agent-Based Campus Novel Coronavirus Infection and Control Simulation
Pei Lv, Quan Zhang, Boya Xu +5
Corona Virus Disease 2019 (COVID-19), due to its extremely high infectivity, has been spreading rapidly around the world and bringing huge influence to socioeconomic development as…
Probability Trajectory: One New Movement Description for Trajectory Prediction
Pei Lv, Hui Wei, Tianxin Gu +4
Trajectory prediction is a fundamental and challenging task for numerous applications, such as autonomous driving and intelligent robots. Currently, most of existing work treat the…