Xiujun Shu

908 total citations
12 papers, 437 citations indexed

About

Xiujun Shu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Xiujun Shu has authored 12 papers receiving a total of 437 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 2 papers in Artificial Intelligence and 2 papers in Biomedical Engineering. Recurrent topics in Xiujun Shu's work include Human Pose and Action Recognition (7 papers), Video Surveillance and Tracking Methods (6 papers) and Multimodal Machine Learning Applications (3 papers). Xiujun Shu is often cited by papers focused on Human Pose and Action Recognition (7 papers), Video Surveillance and Tracking Methods (6 papers) and Multimodal Machine Learning Applications (3 papers). Xiujun Shu collaborates with scholars based in China, Norway and Taiwan. Xiujun Shu's co-authors include Xiao Wang, Yaowei Wang, Feng Wu, Bo Jiang, Yonghong Tian, Ge Li, Qi Tian, Zhipeng Zhang, Shiliang Zhang and Weijian Ruan and has published in prestigious journals such as Neurocomputing, IEEE Transactions on Circuits and Systems for Video Technology and Pattern Recognition Letters.

In The Last Decade

Xiujun Shu

12 papers receiving 428 citations

Peers

Xiujun Shu

CVPR

AI

BE

AE

EEE

Alok Kumar Singh Kushwaha India

Yubin Wu China

Horesh Ben Shitrit Switzerland

Elías Herrero Spain

J. Black United Kingdom

Shafique United States

Qinghai Ding China

Thang Ba Dinh Vietnam

Graeme A. Jones United Kingdom

V. Manohar India

Alok Kumar Singh Kushwaha India

Xiujun Shu

279 ×0.8

CVPR

113 ×1.3

AI

61 ×1.2

BE

25 ×0.6

AE

30 ×0.8

EEE

Citations per year, relative to Xiujun Shu Xiujun Shu (= 1×) peers Alok Kumar Singh Kushwaha

Countries citing papers authored by Xiujun Shu

Since Specialization

Citations

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

Fields of papers citing papers by Xiujun Shu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiujun Shu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiujun Shu. A scholar is included among the top collaborators of Xiujun Shu 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 Xiujun Shu. Xiujun Shu 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:

12 of 12 papers shown

1.

Dai, Tao, et al.. (2023). Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 808–816. 26 indexed citations

2.

Li, Hanjun, et al.. (2023). D3G: Exploring Gaussian Prior for Temporal Sentence Grounding with Glance Annotation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 13688–13700. 12 indexed citations

3.

Wu, Haoqian, Keyu Chen, Haozhe Liu, et al.. (2023). NewsNet: A Novel Dataset for Hierarchical Temporal Segmentation. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 10669–10680. 5 indexed citations

4.

Shu, Xiujun, Ruizhi Qiao, Haoqian Wu, et al.. (2023). Collaborative Noisy Label Cleaner: Learning Scene-aware Trailers for Multi-modal Highlight Detection in Movies. 18898–18907. 6 indexed citations

5.

Wang, Xiao, Xiujun Shu, Shiliang Zhang, et al.. (2022). MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking. IEEE Transactions on Multimedia. 25. 4335–4348. 46 indexed citations

6.

Li, Nannan, Jia-Xing Zhong, Xiujun Shu, & Huiwen Guo. (2022). Weakly-supervised anomaly detection in video surveillance via graph convolutional label noise cleaning. Neurocomputing. 481. 154–167. 21 indexed citations

7.

Wang, Xiao, Xiujun Shu, Zhipeng Zhang, et al.. (2021). Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark. 13758–13768. 141 indexed citations

8.

Shu, Xiujun, Xiao Wang, Shiliang Zhang, et al.. (2021). Large-Scale Spatio-Temporal Person Re-Identification: Algorithms and Benchmark. IEEE Transactions on Circuits and Systems for Video Technology. 32(7). 4390–4403. 59 indexed citations

9.

Shu, Xiujun, Ge Li, Xiao Wang, Weijian Ruan, & Qi Tian. (2021). Semantic-Guided Pixel Sampling for Cloth-Changing Person Re-Identification. IEEE Signal Processing Letters. 28. 1365–1369. 57 indexed citations

10.

Shu, Xiujun, Ge Li, Longhui Wei, et al.. (2021). Diverse part attentive network for video-based person re-identification. Pattern Recognition Letters. 149. 17–23. 10 indexed citations

11.

Li, Ge, et al.. (2021). Learning to disentangle scenes for person re-identification. Image and Vision Computing. 116. 104330–104330. 26 indexed citations

12.

Zhang, Xin, et al.. (2020). Cellular Network Radio Propagation Modeling with Deep Convolutional Neural Networks. 2378–2386. 28 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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