Weiwei Liu

1.3k total citations
67 papers, 911 citations indexed

About

Weiwei Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Weiwei Liu has authored 67 papers receiving a total of 911 indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 21 papers in Computer Vision and Pattern Recognition and 10 papers in Information Systems. Recurrent topics in Weiwei Liu's work include Text and Document Classification Technologies (19 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Speech and Audio Processing (8 papers). Weiwei Liu is often cited by papers focused on Text and Document Classification Technologies (19 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Speech and Audio Processing (8 papers). Weiwei Liu collaborates with scholars based in China, Australia and Singapore. Weiwei Liu's co-authors include Ivor W. Tsang, Xiaobo Shen, Quansen Sun, Wenjie Zhang, Yew-Soon Ong, Fumin Shen, Haobo Wang, Gang Chen, Tianlei Hu and Yunhao Yuan and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Weiwei Liu

63 papers receiving 888 citations

Peers

Weiwei Liu

CVPR

SNP

Lirong Wu China

Jianlin Su China

Naiyang Guan China

Hong Peng China

Yuheng Jia China

Zhangyang Gao China

Grigorios Tzortzis Greece

Zhenyu Wu China

Mulin Chen China

Lirong Wu China

Weiwei Liu

425 ×0.8

237 ×0.5

CVPR

92 ×0.8

28 ×0.3

75 ×0.9

SNP

Citations per year, relative to Weiwei Liu Weiwei Liu (= 1×) peers Lirong Wu

Countries citing papers authored by Weiwei Liu

Since Specialization

Citations

This map shows the geographic impact of Weiwei 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 Weiwei Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiwei Liu more than expected).

Fields of papers citing papers by Weiwei Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weiwei 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 Weiwei Liu. The network helps show where Weiwei Liu may publish in the future.

Co-authorship network of co-authors of Weiwei Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Weiwei Liu. A scholar is included among the top collaborators of Weiwei Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weiwei Liu. Weiwei Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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

20 of 20 papers shown

Shi, Lianghe & Weiwei Liu. (2025). Adversarially robust unsupervised domain adaptation. Artificial Intelligence. 347. 104383–104383.

Li, X. Q., Xin Zou, & Weiwei Liu. (2024). Residual network with self-adaptive time step size. Pattern Recognition. 158. 111008–111008. 1 indexed citations

Liu, Weiwei, et al.. (2024). Unleashing the Potential of Transformer Flow for Photorealistic Face Restoration. 2098–2106. 1 indexed citations

Liu, Weiwei, et al.. (2024). Defying catastrophic forgetting via influence function. Artificial Intelligence. 339. 104261–104261. 1 indexed citations

Wang, Zekai, et al.. (2024). DRF: Improving Certified Robustness via Distributional Robustness Framework. Proceedings of the AAAI Conference on Artificial Intelligence. 38(14). 15752–15760.

Shi, Lianghe & Weiwei Liu. (2024). A Closer Look at Curriculum Adversarial Training: From an Online Perspective. Proceedings of the AAAI Conference on Artificial Intelligence. 38(13). 14973–14981. 2 indexed citations

Shen, Xiaobo, et al.. (2024). Graph Convolutional Multi-Label Hashing for Cross-Modal Retrieval. IEEE Transactions on Neural Networks and Learning Systems. 36(5). 7997–8009. 3 indexed citations

Zou, Xin & Weiwei Liu. (2024). Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data. Proceedings of the AAAI Conference on Artificial Intelligence. 38(15). 17263–17270. 1 indexed citations

Liu, Weiwei, et al.. (2024). Identifying emerging technologies to foresee the future of intelligent ships: a machine learning approach to patent data. International Journal of Technology Policy and Management. 24(4). 417–442. 1 indexed citations

10.

Liu, Weiwei, et al.. (2024). RWESA-GNNR: Fusing Random Walk Embedding and Sentiment Analysis for Graph Neural Network Recommendation. Information Technology And Control. 53(1). 146–159. 2 indexed citations

11.

Liu, Weiwei, et al.. (2023). WAT: Improve the Worst-Class Robustness in Adversarial Training. Proceedings of the AAAI Conference on Artificial Intelligence. 37(12). 14982–14990. 10 indexed citations

12.

Hu, Wenbin, et al.. (2022). Signed network representation with novel node proximity evaluation. Neural Networks. 148. 142–154. 2 indexed citations

13.

Wang, Meng, et al.. (2022). Research on prediction of compressive strength of fly ash and slag mixed concrete based on machine learning. PLoS ONE. 17(12). e0279293–e0279293. 18 indexed citations

14.

Liu, Weiwei. (2019). Copula Multi-label Learning. Neural Information Processing Systems. 32. 6334–6343. 1 indexed citations

15.

Liu, Weiwei & Xiaobo Shen. (2019). Sparse Extreme Multi-label Learning with Oracle Property. International Conference on Machine Learning. 4032–4041. 4 indexed citations

16.

Shen, Xiaobo, Weiwei Liu, Yong Luo, Yew-Soon Ong, & Ivor W. Tsang. (2018). Deep binary prototype multi-label learning. International Joint Conference on Artificial Intelligence. 2675–2681. 3 indexed citations

17.

Shen, Xiaobo, Weiwei Liu, Ivor W. Tsang, Quansen Sun, & Yew-Soon Ong. (2018). Compact Multi-Label Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 13 indexed citations

18.

Shen, Xiaobo, Weiwei Liu, Ivor W. Tsang, Quansen Sun, & Yew-Soon Ong. (2017). Multilabel Prediction via Cross-View Search. IEEE Transactions on Neural Networks and Learning Systems. 29(9). 4324–4338. 64 indexed citations

19.

Liu, Weiwei, Xiaobo Shen, & Ivor W. Tsang. (2017). Sparse Embedded $k$-Means Clustering. UTS ePRESS (University of Technology Sydney). 30. 3319–3327. 21 indexed citations

20.

Liu, Weiwei & Ivor W. Tsang. (2015). On the optimality of classifier chain for multi-label classification. UTS ePRESS (University of Technology Sydney). 28. 712–720. 45 indexed citations

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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