Kai Qiu

835 total citations
28 papers, 453 citations indexed

About

Kai Qiu is a scholar working on Artificial Intelligence, Social Psychology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kai Qiu has authored 28 papers receiving a total of 453 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Social Psychology and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kai Qiu's work include Color perception and design (8 papers), Human Pose and Action Recognition (5 papers) and Video Analysis and Summarization (4 papers). Kai Qiu is often cited by papers focused on Color perception and design (8 papers), Human Pose and Action Recognition (5 papers) and Video Analysis and Summarization (4 papers). Kai Qiu collaborates with scholars based in China, United Kingdom and Pakistan. Kai Qiu's co-authors include Jianlong Fu, Yuantao Gu, Tiejian Li, Houwen Peng, Xiaohan Wang, Xinyue Shen, Dongmei Fu, Song Bai, Xiang Bai and Yongchao Xu and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Access and Pattern Recognition.

In The Last Decade

Kai Qiu

25 papers receiving 430 citations

Peers

Kai Qiu
Jiazhang Wang United States
Peng Dai China
Kai Qiu
Citations per year, relative to Kai Qiu Kai Qiu (= 1×) peers Yanhao Zhang

Countries citing papers authored by Kai Qiu

Since Specialization
Citations

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

Fields of papers citing papers by Kai Qiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Qiu

This figure shows the co-authorship network connecting the top 25 collaborators of Kai Qiu. A scholar is included among the top collaborators of Kai Qiu 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 Kai Qiu. Kai Qiu 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.
Qiu, Kai, et al.. (2025). Identification and analysis of driving factors for product evolution: A text data mining approach. Alexandria Engineering Journal. 126. 143–159. 1 indexed citations
4.
Qiu, Kai, et al.. (2024). Fuzzy Relationship between Kansei Images: A Grey Decision-Making Method for Product Form. Applied Sciences. 14(13). 5728–5728. 1 indexed citations
5.
Wang, Yanhui, Jianmin Bao, Ruoyu Feng, et al.. (2024). MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation. 8414–8424. 4 indexed citations
6.
Qiu, Kai, et al.. (2024). A Simple Variable Frequency and Single-Phase-Shifted Control for the Dual Active Bridge Series Resonant Converter. IEEE Journal of Emerging and Selected Topics in Industrial Electronics. 6(1). 308–326. 3 indexed citations
7.
Feng, Ruoyu, Yanhui Wang, Qi Dai, et al.. (2024). ART•V: Auto-Regressive Text-to-Video Generation with Diffusion Models. 7395–7405. 4 indexed citations
8.
Qiu, Kai, et al.. (2024). Inspiring Designers’ Innovative Thinking: An Evolutionary Design Method for Product Forms. Applied Sciences. 14(17). 7818–7818. 2 indexed citations
9.
Yu, Jianfeng, et al.. (2023). Perturbing BEAMs: EEG adversarial attack to deep learning models for epilepsy diagnosing. BMC Medical Informatics and Decision Making. 23(1). 115–115. 5 indexed citations
10.
Qiu, Kai, et al.. (2023). Weakly-supervised pre-training for 3D human pose estimation via perspective knowledge. Pattern Recognition. 139. 109497–109497. 23 indexed citations
11.
Qiu, Kai, et al.. (2023). Dynamic Response Optimization of a DABSRC Based on Feedforward Control. 1635–1639. 1 indexed citations
12.
Qiu, Kai, et al.. (2021). Intelligent Design of Product Forms Based on Design Cognitive Dynamics and a Cobweb Structure. Computational Intelligence and Neuroscience. 2021(1). 6654717–6654717. 11 indexed citations
13.
Wang, Wenjin, et al.. (2021). Research on Product Primitives Recognition in a Computer-Aided Brand Product Development System. Computer-Aided Design and Applications. 18(6). 1146–1166. 12 indexed citations
14.
15.
Qiu, Kai, et al.. (2019). Learning Recurrent Structure-Guided Attention Network for Multi-person Pose Estimation. 418–423. 8 indexed citations
16.
Xu, Chenfeng, Kai Qiu, Jianlong Fu, et al.. (2019). Learn to Scale: Generating Multipolar Normalized Density Maps for Crowd Counting. 8381–8389. 85 indexed citations
17.
Qiu, Kai, et al.. (2017). Time-Varying Graph Signal Reconstruction. IEEE Journal of Selected Topics in Signal Processing. 11(6). 870–883. 94 indexed citations
18.
Qiu, Kai. (2008). Robust information sharing scheme for federated filter based on fault probability. Systems engineering and electronics. 3 indexed citations
19.
Qiu, Kai. (2006). Fault Detection Method for Federated Filtering Structure Based on the Consistency between the Measurements. Chuangan jishu xuebao. 1 indexed citations
20.
Qiu, Kai. (2005). Method of divergence detection for Kalman filter based on filtering process. Systems engineering and electronics.

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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