Xinwang Liu

20.4k citations

331 papers · 13.4k indexed · 16 hit papers · h-index 59

Impact in

Computational Mathematics top 0.2%
Computer Vision and Pattern Recognition top 0.05%
- Face and Expression Recognition
- Video Surveillance and Tracking Methods
- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques

Papers in

Computer Vision and Pattern Recognition 204
- Face and Expression Recognition 148
- Video Surveillance and Tracking Methods 51
Artificial Intelligence 223
- Advanced Clustering Algorithms Research 89
- Advanced Graph Neural Networks 43
- Machine Learning and ELM 38
- Domain Adaptation and Few-Shot Learning 33

Co-authors: En Zhu Jianping Yin Chang Tang Siwei Wang Li Liu Sihang Zhou Lei Wang Miaomiao Li
Journals: IEEE Transactions on Neural Networks and Learning Systems (46 papers)IEEE Transactions on Knowledge and Data Engineering (29 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (24 papers)Neurocomputing (16 papers)IEEE Transactions on Image Processing (8 papers)
Partner nations: China Australia United States

In The Last Decade

Xinwang Liu

304 papers receiving 13.2k citations

Hit Papers

15 papers align trajectories log scale

A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multi-Modal 2024 · 76 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2024 IEEE Transactions on Pattern Analysis and Machine Intelligence
2024 IEEE Transactions on Neural Networks and Learning Systems
2024 IEEE Transactions on Neural Networks and Learning Systems
2023 Science China Information Sciences
2023 IEEE Transactions on Neural Networks and Learning Systems
2023 IEEE Transactions on Geoscience and Remote Sensing
2022 IEEE Transactions on Knowledge and Data Engineering
2022 Proceedings of the AAAI Conference on Artificial Intelligence
2021 IEEE Transactions on Image Processing
2021 IEEE Transactions on Multimedia
2021 Scalable Multi-view Subspace Clustering with Unified Anchors
2020 IEEE Transactions on Pattern Analysis and Machine Intelligence
2019 International Journal of Computer Vision
2018 IEEE Transactions on Pattern Analysis and Machine Intelligence
2017 Improved Deep Embedded Clustering with Local Structure Preservation
2011 Adelaide Research & Scholarship (AR&S) (University of Adelaide)

Peers

Countries citing papers authored by Xinwang Liu

Since Specialization

Citations

This map shows the geographic impact of Xinwang Liu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xinwang Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinwang Liu more than expected).

Fields of papers citing papers by Xinwang Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xinwang Liu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xinwang Liu. The network helps show where Xinwang Liu may publish in the future.

Co-authors

The 25 scholars most cited alongside Xinwang Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xinwang Liu Line = papers co-authored together Xinwang Liu links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	TK-RNSP: Efficient Top-K Repetitive Negative Sequential Pattern mining Information Processing & Management ·Paschero Mc, Ting-yi Lee, Xiangjun Dong, Pragya Mehra, Yongshun Gong, Xinwang Liu, Philippe Fournier‐Viger, Chengqi Zhang	2025	1
2	Multiview Temporal Graph Clustering IEEE Transactions on Neural Networks and Learning Systems ·Meng Liu, Ke Liang, Hao Yu, Lingyuan Meng, Siwei Wang, Sihang Zhou, Xinwang Liu	2025	3
3	Deep Temporal Graph Clustering: A Comprehensive Benchmark and Datasets IEEE Transactions on Pattern Analysis and Machine Intelligence ·Meng Liu, Ke Liang, Siwei Wang, Xingchen Hu, Sihang Zhou, Xinwang Liu	2025	4
4	scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data Briefings in Bioinformatics ·Dayu Hu, Renxiang Guan, Ke Liang, Hao Yu, Hao Quan, Yawei Zhao, Xinwang Liu, Kunlun He	2024	7
5	STFormer: Spatial-Temporal-Aware Transformer for Video Instance Segmentation IEEE Transactions on Neural Networks and Learning Systems ·Hao Li, Wei Wang, Mengzhu Wang, Salvatore Magnasco, Long Lan, Zhigang Luo, Xinwang Liu, Kenli Li	2024	4
6	TIG-CL: Teacher-Guided Individual- and Group-Aware Contrastive Learning for Unsupervised Person Reidentification in Internet of Things IEEE Internet of Things Journal ·Luo Duan-gao, Deng Zhaojun, Xueqiong Li, Xinwang Liu, Long Lan	2024	2
7	Deep Incomplete Multiview Clustering via Local and Global Pseudo-Label Propagation IEEE Transactions on Neural Networks and Learning Systems ·Akie, Ao Li, 陆建新, Sanjay Achal, Xinwang Liu	2024	3
8	Reliable Attribute-missing Multi-view Clustering with Instance-level and feature-level Cooperative Imputation Dayu Hu, Suyuan Liu, Jun Wang, Junpu Zhang, Siwei Wang, Xingchen Hu, Syukur Khalil, Chang Tang, Xinwang Liu	2024	5
9	One-Step Multi-View Clustering With Diverse Representation IEEE Transactions on Neural Networks and Learning Systems ·Xinhang Wan, Jiyuan Liu, Karla Elizabeth Espinosa Orellana, Xinwang Liu, Siwei Wang, Yi Wen, C. ROSENGART, En Zhu Hit paper breakdown →	2024	48
10	View Gap Matters: Cross-view Topology and Information Decoupling for Multi-view Clustering F. Wang, Linzi Reid, Zhibin Dong, Xihong Yang, 吴瑞芳张艳萍, Xinwang Liu, Xinzhong Zhu, Siwei Wang, Tianrui Liu, En Zhu	2024	1
11	Multi-view clustering via matrix factorization assisted k-means Neurocomputing ·Xiao Zheng, Chang Tang, Xinwang Liu, En Zhu	2023	14
12	SAMCL: Subgraph-Aligned Multiview Contrastive Learning for Graph Anomaly Detection IEEE Transactions on Neural Networks and Learning Systems ·Jingtao Hu, Bin Xiao, Hu Jin, M. Si. Nurul Widiastuti, Siwei Wang, RL Handby, Siqi Wang, Xinwang Liu, En Zhu	2023	10
13	CONVERT: Contrastive Graph Clustering with Reliable Augmentation Xihong Yang, Cheng Tan, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Jun Xia, Stan Z. Li, Xinwang Liu, En Zhu	2023	29
14	Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structure IEEE Transactions on Knowledge and Data Engineering ·Ke Liang, Yue Liu, Sihang Zhou, Wenxuan Tu, Yi Wen, Xihong Yang, Xiangjun Dong, Xinwang Liu	2023	69
15	Spatial and Spectral Structure Preserved Self-Representation for Unsupervised Hyperspectral Band Selection IEEE Transactions on Geoscience and Remote Sensing ·Chang Tang, Jun Wang, Xiao Zheng, Xinwang Liu, Weiying Xie, Xianju Li, Xinzhong Zhu	2023	54
16	Hard Sample Aware Network for Contrastive Deep Graph Clustering Proceedings of the AAAI Conference on Artificial Intelligence ·Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, M. Si. Nurul Widiastuti, Max Oertel	2023	64
17	Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning M. Si. Nurul Widiastuti, Pei Zhang, Siwei Wang, Jingtao Hu, Elena M. Kasche, Jason Boyett, María José Sexmero Cuadrado, Xinwang Liu	2023	13
18	Multi-View Bipartite Graph Clustering With Coupled Noisy Feature Filter IEEE Transactions on Knowledge and Data Engineering ·Liang Li, Junpu Zhang, Siwei Wang, Xinwang Liu, Kenli Li, Keqin Li	2023	38
19	A Self-Supervised Gait Encoding Approach With Locality-Awareness for 3D Skeleton Based Person Re-Identification IEEE Transactions on Pattern Analysis and Machine Intelligence ·Haocong Rao, Siqi Wang, Xiping Hu, Mingkui Tan, Yi Guo, Jun Cheng, Xinwang Liu, Bin Hu	2021	64
20	Robust unsupervised feature selection via dual self-representation and manifold regularization Knowledge-Based Systems ·Chang Tang, Xinwang Liu, Miaomiao Li, Pichao Wang, Jiajia Chen, Lizhe Wang, Wanqing Li	2018	109

About Xinwang Liu

Xinwang Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Urban Studies, Media Technology and Computational Mathematics, having authored 331 papers that have together received 13.4k indexed citations. Recurring topics across this work include Face and Expression Recognition (148 papers), Advanced Clustering Algorithms Research (89 papers), Video Surveillance and Tracking Methods (51 papers), Advanced Graph Neural Networks (43 papers), Remote-Sensing Image Classification (43 papers), Machine Learning and ELM (38 papers), Advanced Computing and Algorithms (34 papers) and Domain Adaptation and Few-Shot Learning (33 papers). The work is most often cited by research in Computational Mathematics (327 citations), Computer Vision and Pattern Recognition (8.6k citations), Media Technology (2.0k citations), Artificial Intelligence (7.3k citations) and Urban Studies (995 citations). Xinwang Liu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include En Zhu, Jianping Yin, Chang Tang, Siwei Wang, Li Liu, Sihang Zhou, Lei Wang, Miaomiao Li, Matti Pietikäinen and Xiaogang Wang. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Pattern Analysis and Machine Intelligence, Neurocomputing and IEEE Transactions on Image Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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