Kan Wu

1.1k total citations · 1 hit paper
10 papers, 532 citations indexed

About

Kan Wu is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Artificial Intelligence. According to data from OpenAlex, Kan Wu has authored 10 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 2 papers in Information Systems and 2 papers in Artificial Intelligence. Recurrent topics in Kan Wu's work include Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (2 papers) and Medical Image Segmentation Techniques (2 papers). Kan Wu is often cited by papers focused on Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (2 papers) and Medical Image Segmentation Techniques (2 papers). Kan Wu collaborates with scholars based in China, United States and Germany. Kan Wu's co-authors include Jianlong Fu, Houwen Peng, Hongyang Chao, Minghao Chen, Bin Yan, Huchuan Lu, Dong Wang, Li Chen, Jing Li and Yanheng Zhou and has published in prestigious journals such as Computers & Graphics, IET Image Processing and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Kan Wu

10 papers receiving 517 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.

Rethinking and Improving Relative Position Encoding for Vision Transformer

2021 224 citations Kan Wu, Houwen Peng et al. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kan Wu China	6	368	117	116	59	49	10	532
Chunjuan Bo China	14	387 1.1×	92 0.8×	80 0.7×	41 0.7×	161 3.3×	33	586
Jacek Naruniec Poland	7	550 1.5×	168 1.4×	68 0.6×	48 0.8×	77 1.6×	19	748
Nima Razavi Switzerland	4	387 1.1×	65 0.6×	100 0.9×	20 0.3×	31 0.6×	4	452
Oksam Chae South Korea	12	431 1.2×	26 0.2×	96 0.8×	22 0.4×	37 0.8×	43	613
Yunzuo Zhang China	13	518 1.4×	139 1.2×	84 0.7×	43 0.7×	88 1.8×	62	700
Erkang Cheng China	12	345 0.9×	78 0.7×	102 0.9×	29 0.5×	41 0.8×	47	532
Tao Sheng China	3	524 1.4×	95 0.8×	131 1.1×	34 0.6×	88 1.8×	4	655
Yiming Cui United States	14	547 1.5×	109 0.9×	143 1.2×	58 1.0×	65 1.3×	21	727

Countries citing papers authored by Kan Wu

Since Specialization

Citations

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

Fields of papers citing papers by Kan Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kan Wu

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Zhang, Jinnian, Houwen Peng, Kan Wu, et al.. (2022). MiniViT: Compressing Vision Transformers with Weight Multiplexing. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 12135–12144. 79 indexed citations

2.

Wu, Kan, et al.. (2022). RollBin: reducing code-size via loop rerolling at binary level. 99–110. 4 indexed citations

3.

Yan, Bin, Houwen Peng, Kan Wu, et al.. (2021). LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search. 15175–15184. 148 indexed citations

4.

Wu, Kan, Houwen Peng, Minghao Chen, Jianlong Fu, & Hongyang Chao. (2021). Rethinking and Improving Relative Position Encoding for Vision Transformer. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 10013–10021. 224 indexed citations breakdown →

5.

Yang, Rui, et al.. (2018). Dance of the Dragonfly: A Vision-Based Agile Aerial Touch Solution for IARC Mission 7. 18. 37–43. 1 indexed citations

6.

Wu, Kan, Jie Tang, & Chenhui Zhang. (2018). Where Have You Been? Inferring Career Trajectory from Academic Social Network. 3592–3598. 1 indexed citations

7.

Wu, Kan & Yizhou Yu. (2018). Automatic object extraction from images using deep neural networks and the level‐set method. IET Image Processing. 12(7). 1131–1141. 13 indexed citations

8.

Qian, Yujie, Jie Tang, & Kan Wu. (2018). Weakly Learning to Match Experts in Online Community. 3841–3847. 8 indexed citations

9.

Wu, Kan, Li Chen, Jing Li, & Yanheng Zhou. (2013). Tooth segmentation on dental meshes using morphologic skeleton. Computers & Graphics. 38. 199–211. 53 indexed citations

10.

Wu, Kan. (2010). Mining Subsidence Prediction Parameters Acquiring with 3D Laser Scanning Data. 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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