541 citations · 1.2k across the 53 of their papers we have counts for
53 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…
FT-HID: A Large Scale RGB-D Dataset for First and Third Person Human Interaction Analysis
Zihui Guo, Yonghong Hou, Pichao Wang +3
Analysis of human interaction is one important research topic of human motion analysis. It has been studied either using first person vision (FPV) or third person vision (TPV). How…
FCL-GAN: A Lightweight and Real-Time Baseline for Unsupervised Blind Image Deblurring
Suiyi Zhao, Zhao Zhang, Richang Hong +3
Blind image deblurring (BID) remains a challenging and significant task. Benefiting from the strong fitting ability of deep learning, paired data-driven supervised BID method has o…
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…
A Central Difference Graph Convolutional Operator for Skeleton-Based Action Recognition
Shuangyan Miao, Yonghong Hou, Zhimin Gao +2
This paper proposes a new graph convolutional operator called central difference graph convolution (CDGC) for skeleton based action recognition. It is not only able to aggregate no…
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…
Zero-sample surface defect detection and classification based on semantic feedback neural network
Yibo Guo, Yiming Fan, Zhiyang Xiang +3
Defect detection and classification technology has changed from traditional artificial visual inspection to current intelligent automated inspection, but most of the current defect…
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…
A self-adapting super-resolution structures framework for automatic design of GAN
Yibo Guo, Haidi Wang, Yiming Fan +2
With the development of deep learning, the single super-resolution image reconstruction network models are becoming more and more complex. Small changes in hyperparameters of the m…
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN
Yibo Guo, Haidi Wang, Yiming Fan +2
With the effective application of deep learning in computer vision, breakthroughs have been made in the research of super-resolution images reconstruction. However, many researches…
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…
Lottery Jackpots Exist in Pre-trained Models
Yuxin Zhang, Mingbao Lin, Yunshan Zhong +2
Network pruning is an effective approach to reduce network complexity with acceptable performance compromise. Existing studies achieve the sparsity of neural networks via time-cons…
Automatic Generation of Large-scale 3D Road Networks based on GIS Data
Hua Wang, Yue Wu, Xu Han +3
How to automatically generate a realistic large-scale 3D road network is a key point for immersive and credible traffic simulations. Existing methods cannot automatically generate…
Revisiting Local Descriptor for Improved Few-Shot Classification
Jun He, Richang Hong, Xueliang Liu +2
Few-shot classification studies the problem of quickly adapting a deep learner to understanding novel classes based on few support images. In this context, recent research efforts…
Crowdsourcing Autonomous Traffic Simulation
Hua Wang, Wenshan Zhao, Zhigang Deng +1
We present an innovative framework, Crowdsourcing Autonomous Traffic Simulation (CATS) framework, in order to safely implement and realize orderly traffic flows. We firstly provide…
Multi-Agent Path Planning based on MPC and DDPG
Junxiao Xue, Xiangyan Kong, Bowei Dong +1
The problem of mixed static and dynamic obstacle avoidance is essential for path planning in highly dynamic environment. However, the paths formed by grid edges can be longer than…
Hybrid-driven Trajectory Prediction Based on Group Emotion
Chaochao Li, Mingliang Xu
We present a hybrid-driven trajectory prediction method based on group emotion. The data driven and model driven methods are combined to make a compromise between the controllabili…
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…
Trear: Transformer-based RGB-D Egocentric Action Recognition
Xiangyu Li, Yonghong Hou, Pichao Wang +3
In this paper, we propose a \textbf{Tr}ansformer-based RGB-D \textbf{e}gocentric \textbf{a}ction \textbf{r}ecognition framework, called Trear. It consists of two modules, inter-fra…
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…
Transformer Guided Geometry Model for Flow-Based Unsupervised Visual Odometry
Xiangyu Li, Yonghong Hou, Pichao Wang +3
Existing unsupervised visual odometry (VO) methods either match pairwise images or integrate the temporal information using recurrent neural networks over a long sequence of images…
An End-to-end Method for Producing Scanning-robust Stylized QR Codes
Hao Su, Jianwei Niu, Xuefeng Liu +4
Quick Response (QR) code is one of the most worldwide used two-dimensional codes.~Traditional QR codes appear as random collections of black-and-white modules that lack visual sema…