Xialei Liu

4.2k total citations · 2 hit papers
56 papers, 2.2k citations indexed

About

Xialei Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Xialei Liu has authored 56 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 25 papers in Computer Vision and Pattern Recognition and 10 papers in Molecular Biology. Recurrent topics in Xialei Liu's work include Domain Adaptation and Few-Shot Learning (20 papers), Multimodal Machine Learning Applications (17 papers) and Advanced Neural Network Applications (8 papers). Xialei Liu is often cited by papers focused on Domain Adaptation and Few-Shot Learning (20 papers), Multimodal Machine Learning Applications (17 papers) and Advanced Neural Network Applications (8 papers). Xialei Liu collaborates with scholars based in China, Spain and Italy. Xialei Liu's co-authors include Joost van de Weijer, Andrew D. Bagdanov, Bartłomiej Twardowski, Marc Masana, Luis Herranz, Hakan Bilen, Weihong Li, Lu Yu, Shangling Jui and Chenshen Wu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and International Journal of Computer Vision.

In The Last Decade

Xialei Liu

46 papers receiving 2.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Class-Incremental Learning: Survey and Performance Evaluation on Image Classification

2022 342 citations Marc Masana, Xialei Liu et al. profile →
RankIQA: Learning from Rankings for No-Reference Image Quality Assessment

2017 311 citations Xialei Liu, Joost van de Weijer et al. Florence Research (University of Florence) profile →

Peers

Xialei Liu

CVPR

AI

MT

RNMI

MB

Yujun Shen China

Yang Long China

Yujia Li China

Hai Su United States

Xinyu Liu China

Mohammed Elmogy Egypt

Jianjun Qian China

Evgin Göçeri Türkiye

Shyam Lal India

Yujun Shen China

Xialei Liu

1.7k ×1.4

CVPR

462 ×0.4

AI

114 ×0.5

MT

90 ×0.6

RNMI

178 ×1.4

MB

Citations per year, relative to Xialei Liu Xialei Liu (= 1×) peers Yujun Shen

Countries citing papers authored by Xialei Liu

Since Specialization

Citations

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

Fields of papers citing papers by Xialei Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xialei Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Xialei Liu. A scholar is included among the top collaborators of Xialei 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 Xialei Liu. Xialei 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

1.

Liu, Xialei, et al.. (2026). Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 40(15). 12259–12267.

2.

Yang, Fei, et al.. (2025). Enhancing Continual Semantic Segmentation via Uncertainty and Class Balance Re-Weighting. IEEE Transactions on Image Processing. 34. 3689–3702.

3.

Liu, Xialei, et al.. (2025). The Role of Indocyanine Green Fluorescence in Complex Laparoscopic Cholecystectomy Navigation. Journal of Visualized Experiments.

4.

Luo, Jin, Liang Li, Xialei Liu, et al.. (2025). Synergistic effects of mannoprotein and ultrasound on the interfacial properties, flavor, and structure of yeast protein. Ultrasonics Sonochemistry. 118. 107372–107372. 2 indexed citations

5.

Wang, Beibei, Xialei Liu, Shugang Li, et al.. (2024). Research note: Changes in chicken egg yolk metabolome during its spray drying and storage. Poultry Science. 103(12). 104453–104453.

6.

Li, Liang, et al.. (2024). A comprehensive review of plant-derived salt substitutes: Classification, mechanism, and application. Food Research International. 194. 114880–114880. 6 indexed citations

7.

Luo, Yuxuan, Runmin Cong, Xialei Liu, Horace H. S. Ip, & Sam Kwong. (2024). Modeling Inner- and Cross-Task Contrastive Relations for Continual Image Classification. IEEE Transactions on Multimedia. 26. 10842–10853. 4 indexed citations

8.

Peng, Zhimao, et al.. (2024). Predictive Sample Assignment for Semantically Coherent Out-of-Distribution Detection. IEEE Transactions on Circuits and Systems for Video Technology. 35(5). 4686–4697.

9.

Liu, Xialei, Zhaomin Zheng, Wenfeng Zhuo, et al.. (2024). Knockdown of RASD1 improves MASLD progression by inhibiting the PI3K/AKT/mTOR pathway. Lipids in Health and Disease. 23(1). 424–424.

10.

Hu, Gan, et al.. (2023). Quantitative N-glycoproteomic analysis of egg yolk powder during thermal processing. Food Research International. 174(Pt 2). 113678–113678. 5 indexed citations

11.

Li, Weihong, Xialei Liu, & Hakan Bilen. (2023). Universal Representations: A Unified Look at Multiple Task and Domain Learning. International Journal of Computer Vision. 132(5). 1521–1545. 13 indexed citations

12.

Zheng, Lin, et al.. (2023). Sequential interactive image segmentation. Computational Visual Media. 9(4). 753–765. 7 indexed citations

13.

Masana, Marc, et al.. (2020). Class-incremental learning: survey and performance evaluation. arXiv (Cornell University). 46 indexed citations

14.

Liu, Xialei, Hao Yang, Avinash Ravichandran, Rahul Bhotika, & Stefano Soatto. (2020). Continual Universal Object Detection. arXiv (Cornell University). 1 indexed citations

15.

He, Kunshan, Xiaopeng Hong, Chongwei Chi, et al.. (2020). A new method of near-infrared fluorescence image-guided hepatectomy for patients with hepatolithiasis: a randomized controlled trial. Surgical Endoscopy. 34(11). 4975–4982. 24 indexed citations

16.

Wu, Chenshen, et al.. (2018). Memory Replay GANs: Learning to Generate New Categories without Forgetting. Neural Information Processing Systems. 31. 5962–5972. 115 indexed citations

17.

Liu, Xialei, Joost van de Weijer, & Andrew D. Bagdanov. (2018). Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. Florence Research (University of Florence). 7661–7669. 203 indexed citations

18.

Zou, Baojia, Xialei Liu, Baimeng Zhang, et al.. (2018). The Expression of FAP in Hepatocellular Carcinoma Cells is Induced by Hypoxia and Correlates with Poor Clinical Outcomes. Journal of Cancer. 9(18). 3278–3286. 59 indexed citations

19.

Li, Jian, Chaonong Cai, Xiaodong Guan, et al.. (2015). Portal vein arterialization promotes liver regeneration after extended partial hepatectomy in a rat model. Journal of Biomedical Research. 29(1). 69–75. 3 indexed citations

20.

Liu, Nan, et al.. (2013). Algorithm of vision tracking for UAV navigation based on multi-constraint KLT. 42(10). 2828–2835. 1 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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