Xiaoxu Li

2.1k total citations · 2 hit papers
71 papers, 1.4k citations indexed

About

Xiaoxu Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Xiaoxu Li has authored 71 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Computer Vision and Pattern Recognition, 44 papers in Artificial Intelligence and 8 papers in Media Technology. Recurrent topics in Xiaoxu Li's work include Domain Adaptation and Few-Shot Learning (37 papers), Advanced Neural Network Applications (19 papers) and Multimodal Machine Learning Applications (13 papers). Xiaoxu Li is often cited by papers focused on Domain Adaptation and Few-Shot Learning (37 papers), Advanced Neural Network Applications (19 papers) and Multimodal Machine Learning Applications (13 papers). Xiaoxu Li collaborates with scholars based in China, United Kingdom and United States. Xiaoxu Li's co-authors include Zhanyu Ma, Dongliang Chang, Jing‐Hao Xue, Jun Guo, Jiyang Xie, Zhuo Sun, Yifeng Ding, Jie Cao, Xiaochen Yang and Yi-Zhe Song and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Chemical Engineering Journal and IEEE Transactions on Image Processing.

In The Last Decade

Xiaoxu Li

60 papers receiving 1.4k 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.

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification

2020 270 citations Dongliang Chang, Jiyang Xie et al. IEEE Transactions on Image Processing profile →
Deep metric learning for few-shot image classification: A Review of recent developments

2023 120 citations Xiaoxu Li, Xiaochen Yang et al. Pattern Recognition profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xiaoxu Li China	17	775	667	183	113	63	71	1.4k
Saurabh Singh India	7	617 0.8×	610 0.9×	84 0.5×	150 1.3×	72 1.1×	12	1.4k
Ivan Krasin United States	5	1.2k 1.6×	808 1.2×	98 0.5×	91 0.8×	43 0.7×	5	1.8k
Neil Alldrin United States	9	1.5k 1.9×	815 1.2×	102 0.6×	93 0.8×	58 0.9×	11	2.1k
Ronghang Hu United States	13	1.5k 1.9×	1.1k 1.7×	106 0.6×	105 0.9×	59 0.9×	17	2.2k
Stefan Popov United States	12	1.4k 1.8×	645 1.0×	103 0.6×	95 0.8×	38 0.6×	15	2.0k
Tom Duerig United States	6	1.1k 1.4×	631 0.9×	87 0.5×	87 0.8×	33 0.5×	6	1.5k
Doyen Sahoo Singapore	11	607 0.8×	428 0.6×	105 0.6×	56 0.5×	64 1.0×	21	1.3k
Mircea Cimpoi United Kingdom	5	1.5k 1.9×	776 1.2×	214 1.2×	107 0.9×	53 0.8×	6	2.0k
Menglin Jia United States	5	570 0.7×	915 1.4×	89 0.5×	167 1.5×	33 0.5×	8	1.5k

Countries citing papers authored by Xiaoxu Li

Since Specialization

Citations

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

Fields of papers citing papers by Xiaoxu Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoxu Li

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

Li, Xiaoxu, Lang Wang, Rui Zhu, et al.. (2025). SRML: Structure-relation mutual learning network for few-shot image classification. Pattern Recognition. 168. 111822–111822. 1 indexed citations

Chen, Ping, Duo Song, Tianying Liu, et al.. (2025). Facet‐dependent Heterogeneous Fenton Reaction Mechanisms on Hematite Nanoparticles for (Photo)catalytic Degradation of Organic Dyes. Advanced Science. 12(43). e08058–e08058.

Li, Xiaoxu, Song Xue, Jiyang Xie, et al.. (2025). Interactive triplet attention for few-shot fine-grained image classification. Neurocomputing. 655. 131377–131377.

Li, Xiaoxu, et al.. (2025). Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data. Advanced Intelligent Systems. 8(2).

Li, Xiaoxu, et al.. (2025). Clarity in chaos: Boosting few-shot classification through information suppression and sparsification. Pattern Recognition. 167. 111726–111726. 1 indexed citations

Liu, Zhongyuan, Dongliang Chang, Aneeshan Sain, et al.. (2025). Self-randomized focuses effectively boost metric-based few-shot classifiers. Pattern Recognition. 164. 111538–111538.

Li, Xiaoxu, et al.. (2025). CDN4: A cross-view Deep Nearest Neighbor Neural Network for fine-grained few-shot classification. Pattern Recognition. 163. 111466–111466. 3 indexed citations

Li, Xiaoxu, et al.. (2024). Analysis of the driving path of e-commerce to high-quality agricultural development in China: empirical evidence from mediating effect models. Frontiers in Sustainable Food Systems. 8. 2 indexed citations

Li, Xiaoxu, et al.. (2024). Rise by Lifting Others: Interacting Features to Uplift Few-Shot Fine-Grained Classification. IEEE Transactions on Circuits and Systems for Video Technology. 35(4). 3094–3103. 1 indexed citations

10.

Zhang, Zhimin, Dongliang Chang, Rui Zhu, et al.. (2024). Query-Aware Cross-Mixup and Cross-Reconstruction for Few-Shot Fine-Grained Image Classification. IEEE Transactions on Circuits and Systems for Video Technology. 35(2). 1276–1286. 4 indexed citations

11.

Li, Xiaoxu, et al.. (2024). Self-reconstruction network for fine-grained few-shot classification. Pattern Recognition. 153. 110485–110485. 15 indexed citations

12.

Li, Xiaoxu, et al.. (2024). Channel-Spatial Support-Query Cross-Attention for Fine-Grained Few-Shot Image Classification. 9175–9183. 1 indexed citations

13.

Li, Xiaoxu, et al.. (2024). A simple scheme to amplify inter-class discrepancy for improving few-shot fine-grained image classification. Pattern Recognition. 156. 110736–110736. 5 indexed citations

14.

Li, Xiaoxu, Xiangyang Wang, Rui Zhu, et al.. (2024). Selectively Augmented Attention Network for Few-Shot Image Classification. IEEE Transactions on Circuits and Systems for Video Technology. 35(2). 1180–1192. 3 indexed citations

15.

Zhang, Zimeng, Xiaoxu Li, Meirong Zong, et al.. (2023). Machine learning assisted phase and size-controlled synthesis of iron oxide particles. Chemical Engineering Journal. 473. 145216–145216. 18 indexed citations

16.

Li, Xiaoxu, et al.. (2023). Locally-Enriched Cross-Reconstruction for Few-Shot Fine-Grained Image Classification. IEEE Transactions on Circuits and Systems for Video Technology. 33(12). 7530–7540. 44 indexed citations

17.

Guo, Yurong, Zhanyu Ma, Xiaoxu Li, & Yuan Dong. (2021). ATRM: Attention-based Task-level Relation Module for GNN-based Few-shot Learning.. arXiv (Cornell University). 1 indexed citations

18.

Li, Xiaoxu, et al.. (2020). BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification. IEEE Transactions on Image Processing. 30. 1318–1331. 132 indexed citations

19.

Li, Xiaoxu, Dongliang Chang, Zhanyu Ma, et al.. (2020). OSLNet: Deep Small-Sample Classification With an Orthogonal Softmax Layer. IEEE Transactions on Image Processing. 29. 6482–6495. 30 indexed citations

20.

Qi, Qi, Xuanjing Shen, Haipeng Chen, & Xiaoxu Li. (2018). SUPERPIXEL SEGMENTATION ALGORITHM OF MRI IMAGES BASED ON STD_SLIC. ICIC express letters. Part B, Applications. 9(1). 69–76. 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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