Yang Wu

3.8k total citations · 1 hit paper
75 papers, 1.3k citations indexed

About

Yang Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Yang Wu has authored 75 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Computer Vision and Pattern Recognition, 22 papers in Artificial Intelligence and 11 papers in Biomedical Engineering. Recurrent topics in Yang Wu's work include Video Surveillance and Tracking Methods (28 papers), Human Pose and Action Recognition (25 papers) and Advanced Image and Video Retrieval Techniques (20 papers). Yang Wu is often cited by papers focused on Video Surveillance and Tracking Methods (28 papers), Human Pose and Action Recognition (25 papers) and Advanced Image and Video Retrieval Techniques (20 papers). Yang Wu collaborates with scholars based in China, Japan and United States. Yang Wu's co-authors include Michihiko Minoh, Masayuki Mukunoki, Zhengkai Jiang, Chengjie Wang, Ying Tai, Yabiao Wang, Fan Yang, Nanning Zheng, Satoshi Nakamura and Sakriani Sakti 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

Yang Wu

68 papers receiving 1.2k citations

Hit Papers

Rethinking Counting and Localization in Crowds: A Purely ... 2021 2026 2022 2024 2021 50 100 150
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.

  1. Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework
    2021 198 citations Qingyu Song, Changan Wang et al. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) profile →

Peers

Yang Wu
Seunghoon Hong South Korea
Peixi Peng China
Liangchen Song United States
Lorenzo Seidenari Italy
Tao Zhao China
De Cheng China
Yifan Sun China
Sergey Ablameyko Belarus
Seunghoon Hong South Korea
Yang Wu
Citations per year, relative to Yang Wu Yang Wu (= 1×) peers Seunghoon Hong

Countries citing papers authored by Yang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Yang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Wu. A scholar is included among the top collaborators of Yang Wu 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 Yang Wu. Yang Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Zhenyu, Bailin Chen, Yang Wu, et al.. (2025). MPDRM: A Multi-Scale Personalized Depression Recognition Model via facial movements. Neurocomputing. 632. 129669–129669.
2.
Wu, Yang, et al.. (2025). Rapid etiological visualization of pleural effusion with bioimpedance spectroscopy tomography. Measurement. 261. 119798–119798.
3.
Yuan, Hao, Yufeng Zhang, Yang Wu, et al.. (2025). Exploring the biological mechanism and clinical value of perineural invasion in pancreatic cancer. Cancer Letters. 613. 217515–217515. 5 indexed citations
4.
Wu, Yang, Li Tian, Tingting Shi, et al.. (2025). Establishment of nomogram of early death in elderly pancreatic cancer patients with liver metastasis. Discover Oncology. 16(1). 333–333. 1 indexed citations
5.
Yang, Yang, et al.. (2024). Multi-Condition Latent Diffusion Network for Scene-Aware Neural Human Motion Prediction. IEEE Transactions on Image Processing. 33. 3907–3920. 2 indexed citations
6.
Wu, Yang, et al.. (2023). Fully Unsupervised Domain-Agnostic Image Retrieval. IEEE Transactions on Circuits and Systems for Video Technology. 34(6). 5077–5090. 4 indexed citations
7.
Fan, Yanbo, Yong Zhang, Yunpeng Bai, et al.. (2023). NOFA: NeRF-based One-shot Facial Avatar Reconstruction. 1–12. 14 indexed citations
8.
Wu, Yang, et al.. (2023). ACNet: Approaching-and-Centralizing Network for Zero-Shot Sketch-Based Image Retrieval. IEEE Transactions on Circuits and Systems for Video Technology. 33(9). 5022–5035. 18 indexed citations
9.
Qi, Zhongang, et al.. (2023). Toward Human Perception-Centric Video Thumbnail Generation. 6653–6664. 1 indexed citations
10.
Zheng, Ziqiang, et al.. (2023). DaCo: domain-agnostic contrastive learning for visual place recognition. Applied Intelligence. 53(19). 21827–21840. 3 indexed citations
11.
Shan, Ying, et al.. (2022). Depth‐Aware Shadow Removal. Computer Graphics Forum. 41(7). 455–464. 1 indexed citations
12.
Liu, Ye, Siyuan Li, Yang Wu, et al.. (2022). UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 3032–3041. 78 indexed citations
13.
Wu, Yang, Dingheng Wang, Xiaotong Lu, et al.. (2022). Efficient Visual Recognition: A Survey on Recent Advances and Brain-inspired Methodologies. arXiv (Cornell University). 19(5). 366–411. 12 indexed citations
14.
Song, Qingyu, Changan Wang, Zhengkai Jiang, et al.. (2021). Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 3345–3354. 198 indexed citations breakdown →
15.
Zheng, Ziqiang, et al.. (2021). Generative Adversarial Network with Multi-branch Discriminator for imbalanced cross-species image-to-image translation. Neural Networks. 141. 355–371. 19 indexed citations
16.
Huang, Xiao, Hongwei Wang, Weiqian Jiang, et al.. (2021). Qualitative Histopathological Classification of Primary Bone Tumors Using Deep Learning: A Pilot Study. Frontiers in Oncology. 11. 735739–735739. 13 indexed citations
17.
Wang, Dingheng, Guangshe Zhao, Guoqi Li, Lei Deng, & Yang Wu. (2020). Compressing 3DCNNs based on tensor train decomposition. Neural Networks. 131. 215–230. 24 indexed citations
18.
Wan, Fangbin, Yang Wu, Xuelin Qian, Yixiong Chen, & Yanwei Fu. (2020). When Person Re-identification Meets Changing Clothes. 3620–3628. 98 indexed citations
19.
Wu, Yang, Michihiko Minoh, Masayuki Mukunoki, & Shihong Lao. (2012). Robust object recognition via third-party collaborative representation. 9 indexed citations
20.
Wu, Yang, Xiaochun Yun, & Jianhua Li. (2005). An Improved Network Intrusion Detection Method based on VQ-SVM.. 583–587. 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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