activity
20102026
most citedAn Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

19 citations · 84 across the 16 of their papers we have counts for

collaborators

18 papers

cs.CV2026

Not All Inputs Are Valid: Towards Open-Set Video Moment Retrieval Using Language

Xiang Fang, Wanlong Fang, Daizong Liu +8

Video Moment Retrieval (VMR) targets to retrieve the specific moment corresponding to a sentence query from an untrimmed video. Although recent works have made remarkable progress…

cs.CV2026

Fewer Steps, Better Performance: Efficient Cross-Modal Clip Trimming for Video Moment Retrieval Using Language

Xiang Fang, Daizong Liu, Wanlong Fang +5

Given an untrimmed video and a sentence query, video moment retrieval using language (VMR) aims to locate a target query-relevant moment. Since the untrimmed video is overlong, alm…

cs.CR2024

The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective

Cheng Wang, Zenghui Yuan, Pan Zhou +3

Mobile Edge Computing (MEC) is a new computing paradigm that enables cloud computing and information technology (IT) services to be delivered at the network's edge. By shifting the…

cs.CV2023★ 2 cited

Transform-Equivariant Consistency Learning for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Jianfeng Dong +6

This paper addresses the temporal sentence grounding (TSG). Although existing methods have made decent achievements in this task, they not only severely rely on abundant video-quer…

cs.CV2023

Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding

Jiahao Zhu, Daizong Liu, Pan Zhou +8

Temporal sentence grounding (TSG) aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence query. All existing works first utilize a spars…

cs.MM2022★ 5 cited

Hierarchical Local-Global Transformer for Temporal Sentence Grounding

Xiang Fang, Daizong Liu, Pan Zhou +2

This paper studies the multimedia problem of temporal sentence grounding (TSG), which aims to accurately determine the specific video segment in an untrimmed video according to a g…

cs.CV2022★ 11 cited

Backdoor Attacks on Crowd Counting

Yuhua Sun, Tailai Zhang, Xingjun Ma +6

Crowd counting is a regression task that estimates the number of people in a scene image, which plays a vital role in a range of safety-critical applications, such as video surveil…

cs.CV2022

Unsupervised Temporal Video Grounding with Deep Semantic Clustering

Daizong Liu, Xiaoye Qu, Yinzhen Wang +5

Temporal video grounding (TVG) aims to localize a target segment in a video according to a given sentence query. Though respectable works have made decent achievements in this task…

cs.CV2022

Memory-Guided Semantic Learning Network for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Xing Di +3

Temporal sentence grounding (TSG) is crucial and fundamental for video understanding. Although the existing methods train well-designed deep networks with a large amount of data, w…

cs.CV2021

Unsupervised Domain Adaptive Person Re-Identification via Human Learning Imitation

Yang Peng, Ping Liu, Yawei Luo +3

Unsupervised domain adaptive person re-identification has received significant attention due to its high practical value. In past years, by following the clustering and finetuning…

cs.CV2021★ 15 cited

Context-aware Biaffine Localizing Network for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Jianfeng Dong +5

This paper addresses the problem of temporal sentence grounding (TSG), which aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence quer…

cs.CV2020★ 2 cited

Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation

Daizong Liu, Shuangjie Xu, Xiao-Yang Liu +3

This paper addresses the task of segmenting class-agnostic objects in semi-supervised setting. Although previous detection based methods achieve relatively good performance, these…

cs.CR2020

Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs

Houxiang Fan, Binghui Wang, Pan Zhou +6

Link prediction in dynamic graphs (LPDG) is an important research problem that has diverse applications such as online recommendations, studies on disease contagion, organizational…

cs.CV2020★ 11 cited

Jointly Cross- and Self-Modal Graph Attention Network for Query-Based Moment Localization

Daizong Liu, Xiaoye Qu, Xiao-Yang Liu +3

Query-based moment localization is a new task that localizes the best matched segment in an untrimmed video according to a given sentence query. In this localization task, one shou…

cs.CV2020

Identity-Aware Attribute Recognition via Real-Time Distributed Inference in Mobile Edge Clouds

Zichuan Xu, Jiangkai Wu, Qiufen Xia +3

With the development of deep learning technologies, attribute recognition and person re-identification (re-ID) have attracted extensive attention and achieved continuous improvemen…

cs.CV2020★ 1 cited

Dynamic Graph Correlation Learning for Disease Diagnosis with Incomplete Labels

Daizong Liu, Shuangjie Xu, Pan Zhou +3

Disease diagnosis on chest X-ray images is a challenging multi-label classification task. Previous works generally classify the diseases independently on the input image without co…

cs.NI2010★ 19 cited

An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

Guowei Wu, Jiankang Ren, Feng Xia +1

A high degree of reliability for critical data transmission is required in body sensor networks (BSNs). However, BSNs are usually vulnerable to channel impairments due to body fadi…

cs.NI2010★ 18 cited

Decentralized Inter-User Interference Suppression in Body Sensor Networks with Non-cooperative Game

Guowei Wu, Jiankang Ren, Feng Xia +2

Body Sensor Networks (BSNs) provide continuous health monitoring and analysis of physiological parameters. A high degree of Quality-of-Service (QoS) for BSN is extremely required.…