Xiantong Zhen

5.2k total citations · 2 hit papers
116 papers, 3.0k citations indexed

About

Xiantong Zhen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Xiantong Zhen has authored 116 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Computer Vision and Pattern Recognition, 53 papers in Artificial Intelligence and 14 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Xiantong Zhen's work include Human Pose and Action Recognition (37 papers), Video Surveillance and Tracking Methods (34 papers) and Domain Adaptation and Few-Shot Learning (30 papers). Xiantong Zhen is often cited by papers focused on Human Pose and Action Recognition (37 papers), Video Surveillance and Tracking Methods (34 papers) and Domain Adaptation and Few-Shot Learning (30 papers). Xiantong Zhen collaborates with scholars based in China, United Arab Emirates and United Kingdom. Xiantong Zhen's co-authors include Ling Shao, Xianbin Cao, Xuelong Li, Baochang Zhang, Shuo Li, Zehao Xiao, Dacheng Tao, Mengyang Yu, Feng Zheng and Yingjun Du and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Xiantong Zhen

108 papers receiving 3.0k 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.

Deep 3D human pose estimation: A review

2021 209 citations Jinbao Wang, Xiantong Zhen et al. profile →
Implicit Diffusion Models for Continuous Super-Resolution

2023 135 citations Xiantong Zhen, Baochang Zhang et al. profile →

Peers

Xiantong Zhen

CVPR

AI

BE

RNMI

MT

Fan Zhu China

Feng Zheng China

R. Venkatesh Babu India

Ning Jia China

Arif Mahmood Pakistan

Linchao Zhu China

Xiaopeng Hong China

Changick Kim South Korea

Yaowei Wang China

Yabiao Wang China

Fan Zhu China

Xiantong Zhen

2.5k ×1.1

CVPR

1.5k ×1.2

AI

302 ×0.8

BE

260 ×1.1

RNMI

250 ×1.1

MT

Citations per year, relative to Xiantong Zhen Xiantong Zhen (= 1×) peers Fan Zhu

Countries citing papers authored by Xiantong Zhen

Since Specialization

Citations

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

Fields of papers citing papers by Xiantong Zhen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiantong Zhen

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

Xiang, Xuezhi, et al.. (2025). Vehicle re-identification with large separable kernel attention and hybrid channel attention. Image and Vision Computing. 155. 105442–105442. 2 indexed citations

2.

Xiang, Xuezhi, et al.. (2025). Self-supervised monocular depth estimation with large kernel attention and dynamic scene perception. Journal of Visual Communication and Image Representation. 108. 104413–104413.

3.

Xiang, Xuezhi, et al.. (2025). Deep scene flow learning from point cloud with Transformer. Neurocomputing. 641. 130350–130350.

4.

Xiang, Xuezhi, et al.. (2025). PVFT-Net: A point-voxel fusion method for self-supervised scene flow estimation with transformer. Neurocomputing. 656. 131508–131508.

5.

Xiong, Huan, Lei Huang, Xiantong Zhen, et al.. (2024). On the Number of Linear Regions of Convolutional Neural Networks With Piecewise Linear Activations. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(7). 5131–5148. 2 indexed citations

6.

Wang, Jinbao, Xiantong Zhen, Jingkuan Song, et al.. (2023). Continuous cross-modal hashing. Pattern Recognition. 142. 109662–109662. 3 indexed citations

7.

Zuo, Liyun, et al.. (2023). Variational Neuron Shifting for Few-Shot Image Classification Across Domains. IEEE Transactions on Multimedia. 26. 1460–1473. 5 indexed citations

8.

Shi, J. L., Jun Xu, Jing Li, et al.. (2023). Gaze Estimation by Attention-Induced Hierarchical Variational Auto-Encoder. IEEE Transactions on Cybernetics. 54(4). 2592–2605. 12 indexed citations

9.

Du, Yingjun, Haoliang Sun, Xiantong Zhen, et al.. (2022). MetaKernel: Learning Variational Random Features With Limited Labels. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(3). 1464–1478. 6 indexed citations

10.

Xu, Jun, et al.. (2022). Latent Domain Generation for Unsupervised Domain Adaptation Object Counting. IEEE Transactions on Multimedia. 25. 1773–1783. 8 indexed citations

11.

Barbieri, Sebastiano, Matthew Orton, Remy Klaassen, et al.. (2022). Deep learning DCE-MRI parameter estimation: Application in pancreatic cancer. Medical Image Analysis. 80. 102512–102512. 30 indexed citations

12.

Li, Ce, Chunyu Xie, Baochang Zhang, et al.. (2021). Memory Attention Networks for Skeleton-Based Action Recognition. IEEE Transactions on Neural Networks and Learning Systems. 33(9). 4800–4814. 110 indexed citations

13.

Xu, Jun, et al.. (2020). Pixel-Level Non-local Image Smoothing With Objective Evaluation. IEEE Transactions on Multimedia. 23. 4065–4078. 37 indexed citations

14.

Zhang, Baochang, et al.. (2019). The Structure Transfer Machine Theory and Applications. IEEE Transactions on Image Processing. 29. 2889–2902. 5 indexed citations

15.

Cao, Xianbin, et al.. (2018). Long-Short-Term Features for Dynamic Scene Classification. IEEE Transactions on Circuits and Systems for Video Technology. 29(4). 1038–1047. 23 indexed citations

16.

Jiang, Xiaolong, Xiantong Zhen, Baochang Zhang, Jian Yang, & Xianbin Cao. (2018). Deep Collaborative Tracking Networks.. British Machine Vision Conference. 87. 4 indexed citations

17.

Yue, Lei, et al.. (2018). Attentional Alignment Networks.. British Machine Vision Conference. 208. 16 indexed citations

18.

Zhen, Xiantong, et al.. (2018). Cognitive Assessment Prediction in Alzheimer’s Disease by Multi-Layer Multi-Target Regression. Neuroinformatics. 16(3-4). 285–294. 22 indexed citations

19.

Zhen, Xiantong, Heye Zhang, Ali Islam, et al.. (2016). Direct and simultaneous estimation of cardiac four chamber volumes by multioutput sparse regression. Medical Image Analysis. 36. 184–196. 33 indexed citations

20.

Li, Jing, Xiantong Zhen, Xianzeng Liu, & Gaoxiang Ouyang. (2014). Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients. The Scientific World JOURNAL. 2014. 1–6. 4 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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