Pingyang Dai

1.2k total citations · 1 hit paper
19 papers, 749 citations indexed

About

Pingyang Dai is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Pingyang Dai has authored 19 papers receiving a total of 749 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 3 papers in Biomedical Engineering and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Pingyang Dai's work include Video Surveillance and Tracking Methods (14 papers), Human Pose and Action Recognition (7 papers) and Advanced Neural Network Applications (4 papers). Pingyang Dai is often cited by papers focused on Video Surveillance and Tracking Methods (14 papers), Human Pose and Action Recognition (7 papers) and Advanced Neural Network Applications (4 papers). Pingyang Dai collaborates with scholars based in China, Sweden and Taiwan. Pingyang Dai's co-authors include Rongrong Ji, Qiong Wu, Yuyu Huang, Haibin Wang, Yongjian Wu, Chia‐Wen Lin, Feiyue Huang, Bineng Zhong, Jie Chen and Peixian Chen and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems and Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy.

In The Last Decade

Pingyang Dai

18 papers receiving 742 citations

Hit Papers

Cross-Modality Person Re-Identification with Generative A... 2018 2026 2020 2023 2018 100 200 300
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. Cross-Modality Person Re-Identification with Generative Adversarial Training
    2018 301 citations Pingyang Dai, Rongrong Ji et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pingyang Dai China 9 707 221 65 64 42 19 749
Guan’an Wang China 7 792 1.1× 234 1.1× 67 1.0× 43 0.7× 50 1.2× 13 842
Zhanxiang Feng China 8 343 0.5× 70 0.3× 51 0.8× 19 0.3× 34 0.8× 13 370
Shiyu Xuan China 7 421 0.6× 102 0.5× 128 2.0× 13 0.2× 63 1.5× 14 474
Shane Brennan United States 7 742 1.0× 289 1.3× 56 0.9× 6 0.1× 42 1.0× 9 786
Shaul Oron Israel 5 467 0.7× 18 0.1× 110 1.7× 18 0.3× 38 0.9× 7 498
Xuetao Feng China 7 240 0.3× 55 0.2× 32 0.5× 17 0.3× 24 0.6× 24 272
S.L. Dockstader United States 8 356 0.5× 91 0.4× 61 0.9× 6 0.1× 17 0.4× 18 420
Caglayan Dicle United States 5 247 0.3× 22 0.1× 48 0.7× 15 0.2× 28 0.7× 6 292

Countries citing papers authored by Pingyang Dai

Since Specialization
Citations

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

Fields of papers citing papers by Pingyang Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pingyang Dai

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

All Works

19 of 19 papers shown
1.
Dai, Pingyang, et al.. (2024). Occluded Person Re-identification via Saliency-Guided Patch Transfer. Proceedings of the AAAI Conference on Artificial Intelligence. 38(5). 5070–5078. 14 indexed citations
2.
Wu, Qiong, et al.. (2024). CycleTrans: Learning Neutral Yet Discriminative Features via Cycle Construction for Visible- Infrared Person Re-Identification. IEEE Transactions on Neural Networks and Learning Systems. 36(3). 5469–5479. 5 indexed citations
3.
Pan, Wensheng, Yan Zhang, Xiawu Zheng, et al.. (2024). Semi-Supervised Blind Image Quality Assessment through Knowledge Distillation and Incremental Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(5). 4388–4396. 6 indexed citations
4.
Tan, Lei, et al.. (2024). Attention Disturbance and Dual-Path Constraint Network for Occluded Person Re-identification. Proceedings of the AAAI Conference on Artificial Intelligence. 38(6). 6198–6206. 10 indexed citations
5.
Dai, Pingyang, Rongrong Ji, Lei Tan, et al.. (2024). RLE: A Unified Perspective of Data Augmentation for Cross-Spectral Re-Identification. 126977–126996. 1 indexed citations
6.
Li, Jiahan, Pingyang Dai, Qixiang Ye, et al.. (2023). Unsupervised Domain Adaptation on Person Reidentification Via Dual-Level Asymmetric Mutual Learning. IEEE Transactions on Neural Networks and Learning Systems. 36(1). 1371–1382. 2 indexed citations
7.
8.
Dai, Pingyang, et al.. (2022). Dynamic Prototype Mask for Occluded Person Re-Identification. Proceedings of the 30th ACM International Conference on Multimedia. 531–540. 57 indexed citations
9.
Dai, Pingyang, Peixian Chen, Qiong Wu, et al.. (2021). Disentangling Task-Oriented Representations for Unsupervised Domain Adaptation. IEEE Transactions on Image Processing. 31. 1012–1026. 12 indexed citations
10.
Chen, Peixian, Pingyang Dai, Jianzhuang Liu, et al.. (2021). Dual Distribution Alignment Network for Generalizable Person Re-Identification. Proceedings of the AAAI Conference on Artificial Intelligence. 35(2). 1054–1062. 36 indexed citations
11.
Chen, Peixian, Pingyang Dai, Jianzhuang Liu, et al.. (2021). Occlude Them All: Occlusion-Aware Attention Network for Occluded Person Re-ID. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 11813–11822. 87 indexed citations
12.
Wu, Qiong, Pingyang Dai, Jie Chen, et al.. (2021). Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification. 4328–4337. 190 indexed citations
13.
Wu, Qiong, Pingyang Dai, Peixian Chen, & Yuyu Huang. (2019). Deep adversarial data augmentation with attribute guided for person re-identification. Signal Image and Video Processing. 15(4). 655–662. 12 indexed citations
14.
Xie, Yi, Pingyang Dai, Shuyi Wang, et al.. (2019). How to achieve auto-identification in Raman analysis by spectral feature extraction & Adaptive Hypergraph. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 222. 117086–117086. 7 indexed citations
15.
Dai, Pingyang, Rongrong Ji, Haibin Wang, Qiong Wu, & Yuyu Huang. (2018). Cross-Modality Person Re-Identification with Generative Adversarial Training. 677–683. 301 indexed citations breakdown →
16.
Dai, Pingyang, et al.. (2014). Bag of Features with Dense Sampling for Visual Tracking ⋆.
17.
Dai, Pingyang, et al.. (2014). Online co-training ranking SVM for visual tracking. Zenodo (CERN European Organization for Nuclear Research). 33. 6568–6572. 1 indexed citations
18.
Wang, Lan, et al.. (2013). Visual Tracking Based on Compressive Sensing MCMC Sampling. 77. 4288–4293. 1 indexed citations
19.
Dai, Pingyang, et al.. (2013). Robust visual tracking via part-based sparsity model. 1. 1803–1806. 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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