Zhanghan Ke

2.0k total citations · 1 hit paper
10 papers, 858 citations indexed

About

Zhanghan Ke is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Instrumentation. According to data from OpenAlex, Zhanghan Ke has authored 10 papers receiving a total of 858 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 2 papers in Artificial Intelligence and 1 paper in Instrumentation. Recurrent topics in Zhanghan Ke's work include Image Enhancement Techniques (4 papers), Advanced Neural Network Applications (3 papers) and Advanced Vision and Imaging (2 papers). Zhanghan Ke is often cited by papers focused on Image Enhancement Techniques (4 papers), Advanced Neural Network Applications (3 papers) and Advanced Vision and Imaging (2 papers). Zhanghan Ke collaborates with scholars based in Hong Kong, China and United States. Zhanghan Ke's co-authors include Rynson W. H. Lau, Lei Zhu, Xinjiang Wang, Wei Zhang, Qiong Yan, Jimmy Ren, Kaican Li, Ke Xu, Yuhao Liu and Nanxuan Zhao and has published in prestigious journals such as IEEE Transactions on Image Processing, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and arXiv (Cornell University).

In The Last Decade

Zhanghan Ke

10 papers receiving 838 citations

Hit Papers

BiFormer: Vision Transformer with Bi-Level Routing Attention 2023 2026 2024 2025 2023 100 200 300 400 500
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. BiFormer: Vision Transformer with Bi-Level Routing Attention
    2023 569 citations Lei Zhu, Xinjiang Wang et al. profile →

Peers

Zhanghan Ke
Diganta Misra India
Asra Aslam Ireland
Lingxiao Yang China
Zhiqi Li China
Shoubhik Debnath United States
Yingtian Zou Singapore
Jun Hao Liew Singapore
Zhuofan Xia China
Diganta Misra India
Zhanghan Ke
Citations per year, relative to Zhanghan Ke Zhanghan Ke (= 1×) peers Diganta Misra

Countries citing papers authored by Zhanghan Ke

Since Specialization
Citations

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

Fields of papers citing papers by Zhanghan Ke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhanghan Ke

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

All Works

10 of 10 papers shown
1.
Liang, Dong, et al.. (2025). VODiff: Controlling Object Visibility Order in Text-to-Image Generation. 18379–18389. 1 indexed citations
2.
Liu, Yuhao, Zhanghan Ke, Ke Xu, et al.. (2024). Recasting Regional Lighting for Shadow Removal. Proceedings of the AAAI Conference on Artificial Intelligence. 38(4). 3810–3818. 4 indexed citations
3.
Ke, Zhanghan, Yuhao Liu, Lei Zhu, Nanxuan Zhao, & Rynson W. H. Lau. (2023). Neural Preset for Color Style Transfer. 14173–14182. 15 indexed citations
4.
Liu, Yuhao, Qing Guo, Lan Fu, et al.. (2023). Structure-Informed Shadow Removal Networks. IEEE Transactions on Image Processing. 32. 5823–5836. 5 indexed citations
5.
Zhu, Lei, Xinjiang Wang, Zhanghan Ke, Wei Zhang, & Rynson W. H. Lau. (2023). BiFormer: Vision Transformer with Bi-Level Routing Attention. 10323–10333. 569 indexed citations breakdown →
6.
Ke, Zhanghan, et al.. (2022). MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition. Proceedings of the AAAI Conference on Artificial Intelligence. 36(1). 1140–1147. 68 indexed citations
7.
Zhu, Lei, Ke Xu, Zhanghan Ke, & Rynson W. H. Lau. (2021). Mitigating Intensity Bias in Shadow Detection via Feature Decomposition and Reweighting. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 4682–4691. 40 indexed citations
8.
Ke, Zhanghan, et al.. (2020). Is a Green Screen Really Necessary for Real-Time Human Matting?. arXiv (Cornell University). 3 indexed citations
9.
Qiu, Di, Jin Zeng, Zhanghan Ke, Wenxiu Sun, & C.G. Yang. (2020). Towards Geometry Guided Neural Relighting with Flash Photography. 38. 1137–1146. 4 indexed citations
10.
Ke, Zhanghan, et al.. (2019). Dual Student: Breaking the Limits of the Teacher in Semi-Supervised Learning. 6727–6735. 149 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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