63 citations · 212 across the 24 of their papers we have counts for
24 papers
Focal and Global Spatial-Temporal Transformer for Skeleton-based Action Recognition
Zhimin Gao, Peitao Wang, Pei Lv +5
Despite great progress achieved by transformer in various vision tasks, it is still underexplored for skeleton-based action recognition with only a few attempts. Besides, these met…
TraInterSim: Adaptive and Planning-Aware Hybrid-Driven Traffic Intersection Simulation
Pei Lv, Xinming Pei, Xinyu Ren +3
Traffic intersections are important scenes that can be seen almost everywhere in the traffic system. Currently, most simulation methods perform well at highways and urban traffic n…
D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights
Yuzhen Zhang, Wentong Wang, Weizhi Guo +4
A profound understanding of inter-agent relationships and motion behaviors is important to achieve high-quality planning when navigating in complex scenarios, especially at urban t…
Multi-Agent Broad Reinforcement Learning for Intelligent Traffic Light Control
Ruijie Zhu, Lulu Li, Shuning Wu +3
Intelligent Traffic Light Control System (ITLCS) is a typical Multi-Agent System (MAS), which comprises multiple roads and traffic lights.Constructing a model of MAS for ITLCS is t…
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…
Personality-Aware Probabilistic Map for Trajectory Prediction of Pedestrians
Chaochao Li, Pei Lv, Mingliang Xu +4
We present a novel trajectory prediction algorithm for pedestrians based on a personality-aware probabilistic feature map. This map is computed using a spatial query structure and…
Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization
Pei Lv, Haiyu Yu, Junxiao Xue +5
Localizing objects with weak supervision in an image is a key problem of the research in computer vision community. Many existing Weakly-Supervised Object Localization (WSOL) appro…
ACSEE: Antagonistic Crowd Simulation Model with Emotional Contagion and Evolutionary Game Theory
Chaochao Li, Pei Lv, Dinesh Manocha +4
Antagonistic crowd behaviors are often observed in cases of serious conflict. Antagonistic emotions, which is the typical psychological state of agents in different roles (i.e. cop…
Abnormal Event Detection and Location for Dense Crowds using Repulsive Forces and Sparse Reconstruction
Pei Lv, Shunhua Liu, Mingliang Xu +1
This paper proposes a method based on repulsive forces and sparse reconstruction for the detection and location of abnormal events in crowded scenes. In order to avoid the challeng…
MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects
Lisha Cui, Rui Ma, Pei Lv +4
For most of the object detectors based on multi-scale feature maps, the shallow layers are rich in fine spatial information and thus mainly responsible for small object detection.…
USAR: an Interactive User-specific Aesthetic Ranking Framework for Images
Pei Lv, Meng Wang, Yongbo Xu +5
When assessing whether an image is of high or low quality, it is indispensable to take personal preference into account. Existing aesthetic models lay emphasis on hand-crafted feat…
Bi-directional Graph Structure Information Model for Multi-Person Pose Estimation
Jing Wang, Ze Peng, Pei Lv +3
In this paper, we propose a novel multi-stage network architecture with two branches in each stage to estimate multi-person poses in images. The first branch predicts the confidenc…
Depth Information Guided Crowd Counting for Complex Crowd Scenes
Mingliang Xu, Zhaoyang Ge, Xiaoheng Jiang +4
It is important to monitor and analyze crowd events for the sake of city safety. In an EDOF (extended depth of field) image with a crowded scene, the distribution of people is high…
Improving Aviation Safety using Synthetic Vision System integrated with Eye-tracking Devices
Mingliang Xu, Yibo Guo, Bailin Yang +4
By collecting the data of eyeball movement of pilots, it is possible to monitor pilot's operation in the future flight in order to detect potential accidents. In this paper, we des…
ART-UP: A Novel Method for Generating Scanning-robust Aesthetic QR codes
Mingliang Xu, Qingfeng Li, Jianwei Niu +4
QR codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the vis…
Stylize Aesthetic QR Code
Mingliang Xu, Hao Su, Yafei Li +5
With the continued proliferation of smart mobile devices, Quick Response (QR) code has become one of the most-used types of two-dimensional code in the world. Aiming at beautifying…
Crowd Behavior Simulation with Emotional Contagion in Unexpected Multi-hazard Situations
Mingliang Xu, Xiaozheng Xie, Pei Lv +6
In this paper we present a novel crowd simulation method by modeling the generation and contagion of panic emotion under multi-hazard circumstances. Specifically, we first classify…
Emotion-Based Crowd Simulation Model Based on Physical Strength Consumption for Emergency Scenarios
Mingliang Xu, Chaochao Li, Pei Lv +4
Increasing attention is being given to the modeling and simulation of traffic flow and crowd movement, two phenomena that both deal with interactions between pedestrians and cars i…