64 citations · 107 across the 14 of their papers we have counts for
14 papers
Audio-visual Representation Learning for Anomaly Events Detection in Crowds
Junyu Gao, Maoguo Gong, Xuelong Li
In recent years, anomaly events detection in crowd scenes attracts many researchers' attention, because of its importance to public safety. Existing methods usually exploit visual…
Self-adaptive Multi-task Particle Swarm Optimization
Xiaolong Zheng, Deyun Zhou, Na Li +3
Multi-task optimization (MTO) studies how to simultaneously solve multiple optimization problems for the purpose of obtaining better performance on each problem. Over the past few…
Hierarchical Multimodal Transformer to Summarize Videos
Bin Zhao, Maoguo Gong, Xuelong Li
Although video summarization has achieved tremendous success benefiting from Recurrent Neural Networks (RNN), RNN-based methods neglect the global dependencies and multi-hop relati…
Congested Crowd Instance Localization with Dilated Convolutional Swin Transformer
Junyu Gao, Maoguo Gong, Xuelong Li
Crowd localization is a new computer vision task, evolved from crowd counting. Different from the latter, it provides more precise location information for each instance, not just…
Towards Explainable Multi-Party Learning: A Contrastive Knowledge Sharing Framework
Yuan Gao, Jiawei Li, Maoguo Gong +2
Multi-party learning provides solutions for training joint models with decentralized data under legal and practical constraints. However, traditional multi-party learning approache…
AudioVisual Video Summarization
Bin Zhao, Maoguo Gong, Xuelong Li
Audio and vision are two main modalities in video data. Multimodal learning, especially for audiovisual learning, has drawn considerable attention recently, which can boost the per…
An attention-based unsupervised adversarial model for movie review spam detection
Yuan Gao, Maoguo Gong, Yu Xie +1
With the prevalence of the Internet, online reviews have become a valuable information resource for people. However, the authenticity of online reviews remains a concern, and decep…
Feature Weighted Non-negative Matrix Factorization
Mulin Chen, Maoguo Gong, Xuelong Li
Non-negative Matrix Factorization (NMF) is one of the most popular techniques for data representation and clustering, and has been widely used in machine learning and data analysis…
AsymptoticNG: A regularized natural gradient optimization algorithm with look-ahead strategy
Zedong Tang, Fenlong Jiang, Junke Song +5
Optimizers that further adjust the scale of gradient, such as Adam, Natural Gradient (NG), etc., despite widely concerned and used by the community, are often found poor generaliza…
Differentially Private ADMM Algorithms for Machine Learning
Tao Xu, Fanhua Shang, Yuanyuan Liu +3
In this paper, we study efficient differentially private alternating direction methods of multipliers (ADMM) via gradient perturbation for many machine learning problems. For smoot…
Locality Preserving Dense Graph Convolutional Networks with Graph Context-Aware Node Representations
Wenfeng Liu, Maoguo Gong, Zedong Tang +1
Graph convolutional networks (GCNs) have been widely used for representation learning on graph data, which can capture structural patterns on a graph via specifically designed conv…
Nucleus Neural Network: A Data-driven Self-organized Architecture
Jia Liu, Maoguo Gong, Haibo He
Artificial neural networks which are inspired from the learning mechanism of brain have achieved great successes in many problems, especially those with deep layers. In this paper,…
Semi-supervised Multimodal Hashing
Dayong Tian, Maoguo Gong, Deyun Zhou +2
Retrieving nearest neighbors across correlated data in multiple modalities, such as image-text pairs on Facebook and video-tag pairs on YouTube, has become a challenging task due t…
Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors
Yu Zhao, Rennong Yang, Guillaume Chevalier +1
Human activity recognition (HAR) has become a popular topic in research because of its wide application. With the development of deep learning, new ideas have appeared to address H…