Kaibing Zhang

2.8k total citations · 1 hit paper
97 papers, 2.2k citations indexed

About

Kaibing Zhang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Kaibing Zhang has authored 97 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Computer Vision and Pattern Recognition, 41 papers in Media Technology and 20 papers in Artificial Intelligence. Recurrent topics in Kaibing Zhang's work include Advanced Image Processing Techniques (43 papers), Image Processing Techniques and Applications (27 papers) and Advanced Vision and Imaging (26 papers). Kaibing Zhang is often cited by papers focused on Advanced Image Processing Techniques (43 papers), Image Processing Techniques and Applications (27 papers) and Advanced Vision and Imaging (26 papers). Kaibing Zhang collaborates with scholars based in China, Australia and Germany. Kaibing Zhang's co-authors include Xinbo Gao, Xuelong Li, Dacheng Tao, Dacheng Tao, Zhonghua Liu, Weihua Ou, Dacheng Tao, Jie Li, Haijun Wang and Zhihui Lai and has published in prestigious journals such as IEEE Transactions on Image Processing, Expert Systems with Applications and IEEE Access.

In The Last Decade

Kaibing Zhang

81 papers receiving 2.1k 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.

Single Image Super-Resolution With Non-Local Means and Steering Kernel Regression

2012 466 citations Kaibing Zhang, Xinbo Gao et al. profile →

Peers

Kaibing Zhang

CVPR

MT

CM

AI

IME

Hui Zeng China

Hongwei Yong Hong Kong

Kin Gwn Lore United States

L. Ganesan India

Qi Shan United States

Delu Zeng China

Wenxiu Sun Hong Kong

Yang Xu China

In-So Kweon South Korea

Jiahao Pang Hong Kong

Hui Zeng China

Kaibing Zhang

1.6k ×0.9

CVPR

556 ×0.5

MT

103 ×0.5

CM

110 ×0.6

AI

63 ×0.5

IME

Citations per year, relative to Kaibing Zhang Kaibing Zhang (= 1×) peers Hui Zeng

Countries citing papers authored by Kaibing Zhang

Since Specialization

Citations

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

Fields of papers citing papers by Kaibing Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaibing Zhang

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

All Works

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20 of 20 papers shown

1.

Zhang, Kaibing, et al.. (2025). Process simulation and techno-economic analysis of 400 t/d pilot plant for municipal sewage sludge drying and combustion. Process Safety and Environmental Protection. 196. 106833–106833. 1 indexed citations

2.

Hou, Xingsong, et al.. (2025). Learning scalable Omni-scale distribution for crowd counting. Journal of Visual Communication and Image Representation. 107. 104387–104387.

3.

Yin, Pengfei, Zhonghua Liu, Weihua Ou, & Kaibing Zhang. (2024). Unsupervised Vast-Receptive-Field attention for blind Super-Resolution. Expert Systems with Applications. 268. 126190–126190.

4.

Zhang, Kaibing, et al.. (2024). ADT: Person re-identification based on efficient attention mechanism and single-channel dual-channel fusion with transformer features aggregation. Expert Systems with Applications. 261. 125489–125489. 3 indexed citations

5.

Zhang, Kaibing, et al.. (2024). RMANet: Refined-mixed attention network for progressive low-light image enhancement. Signal Processing. 227. 109689–109689.

6.

Zhang, Kaibing, Dongdong Zheng, Jie Li, Xinbo Gao, & Jian Lü. (2023). Coupled discriminative manifold alignment for low-resolution face recognition. Pattern Recognition. 147. 110049–110049. 7 indexed citations

7.

Hu, Yanting, Yuanfei Huang, & Kaibing Zhang. (2023). Multi-scale information distillation network for efficient image super-resolution. Knowledge-Based Systems. 275. 110718–110718. 16 indexed citations

8.

Chen, Jinguang, et al.. (2023). Uncertainty awareness with adaptive propagation for multi-view stereo. Applied Intelligence. 53(21). 26230–26239.

9.

Zhang, Kaibing, et al.. (2023). Learning cascade regression for super-resolution image quality assessment. Applied Intelligence. 53(22). 27304–27322. 1 indexed citations

10.

Zhang, Kaibing, et al.. (2023). SECANet: A structure‐enhanced attention network with dual‐domain contrastive learning for scene text image super‐resolution. Electronics Letters. 59(24). 1 indexed citations

11.

Zhang, Kaibing, et al.. (2023). A lightweight multi‐branch network for low‐light image enhancement. Electronics Letters. 59(9).

12.

Ou, Weihua, et al.. (2023). Robust manifold discriminative distribution adaptation for transfer subspace learning. Expert Systems with Applications. 238. 122117–122117. 7 indexed citations

13.

Zhang, Ting, et al.. (2023). Deformable channel non‐local network for crowd counting. Electronics Letters. 59(10). 4 indexed citations

14.

Lü, Jian, et al.. (2023). Multi‐temporal scale aggregation refinement graph convolutional network for skeleton‐based action recognition. Computer Animation and Virtual Worlds. 35(1). 4 indexed citations

15.

Zhang, Tingyue, et al.. (2022). Joint channel-spatial attention network for super-resolution image quality assessment. Applied Intelligence. 52(15). 17118–17132. 10 indexed citations

16.

Lü, Jian, et al.. (2022). Bi-Directional Style Adaptation Network for Person Re-Identification. IEEE Sensors Journal. 22(12). 12339–12347. 7 indexed citations

17.

Li, Minqi, et al.. (2022). Multi-level landmark-guided deep network for face super-resolution. Neural Networks. 152. 276–286. 14 indexed citations

18.

Li, Minqi, Xiangjian He, Kin‐Man Lam, Kaibing Zhang, & Junfeng Jing. (2021). Face hallucination based on cluster consistent dictionary learning. IET Image Processing. 15(12). 2841–2853. 1 indexed citations

19.

Zhang, Kaibing, et al.. (2020). Fabric defect detection using saliency of multi‐scale local steering kernel. IET Image Processing. 14(7). 1265–1272. 11 indexed citations

20.

Zhang, Kaibing, et al.. (2018). Fabric Defect Detection Using Salience Metric for Color Dissimilarity and Positional Aggregation. IEEE Access. 6. 49170–49181. 50 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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