Kuiyuan Yang

5.7k total citations · 1 hit paper
45 papers, 2.3k citations indexed

About

Kuiyuan Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Kuiyuan Yang has authored 45 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 9 papers in Aerospace Engineering. Recurrent topics in Kuiyuan Yang's work include Advanced Image and Video Retrieval Techniques (35 papers), Image Retrieval and Classification Techniques (18 papers) and Advanced Neural Network Applications (14 papers). Kuiyuan Yang is often cited by papers focused on Advanced Image and Video Retrieval Techniques (35 papers), Image Retrieval and Classification Techniques (18 papers) and Advanced Neural Network Applications (14 papers). Kuiyuan Yang collaborates with scholars based in China, United States and United Kingdom. Kuiyuan Yang's co-authors include Zhiwei Li, Kun Yu, Chi Zhang, Hao Zhang, Xian‐Sheng Hua, Meng Wang, Wei Yu, Hongxun Yao, Tao Mei and Xiangtai Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Kuiyuan Yang

45 papers receiving 2.3k citations

Hit Papers

DenseASPP for Semantic Segmentation in Street Scenes 2018 2026 2020 2023 2018 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kuiyuan Yang China 18 1.8k 643 323 160 156 45 2.3k
Varun Jampani United States 21 2.4k 1.3× 717 1.1× 314 1.0× 192 1.2× 174 1.1× 65 3.1k
Zhuliang Yao China 8 1.6k 0.9× 752 1.2× 375 1.2× 218 1.4× 156 1.0× 9 2.5k
Jiachen Lu China 8 1.7k 0.9× 723 1.1× 495 1.5× 282 1.8× 147 0.9× 32 2.6k
Zhongyue Zhang China 8 1.7k 1.0× 905 1.4× 368 1.1× 265 1.7× 183 1.2× 23 2.9k
Fadi Dornaika Spain 29 1.9k 1.0× 716 1.1× 367 1.1× 148 0.9× 251 1.6× 228 2.8k
Tianfei Zhou China 28 2.1k 1.2× 1.1k 1.6× 316 1.0× 173 1.1× 144 0.9× 61 2.9k
Shanghua Gao China 11 1.7k 0.9× 687 1.1× 420 1.3× 291 1.8× 172 1.1× 14 2.7k
Zheng-Ning Liu China 7 1.3k 0.7× 583 0.9× 379 1.2× 218 1.4× 181 1.2× 10 2.5k
Zhenda Xie China 7 1.4k 0.8× 786 1.2× 345 1.1× 239 1.5× 168 1.1× 10 2.4k

Countries citing papers authored by Kuiyuan Yang

Since Specialization
Citations

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

Fields of papers citing papers by Kuiyuan Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kuiyuan Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Kuiyuan Yang. A scholar is included among the top collaborators of Kuiyuan Yang 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 Kuiyuan Yang. Kuiyuan Yang 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.
Li, Xiangtai, Jiangning Zhang, Yibo Yang, et al.. (2023). Sfnet: Faster and Accurate Semantic Segmentation Via Semantic Flow. International Journal of Computer Vision. 132(2). 466–489. 30 indexed citations
2.
Li, Xiangtai, Hao He, Yibo Yang, et al.. (2022). Improving Video Instance Segmentation via Temporal Pyramid Routing. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(5). 1–8. 4 indexed citations
3.
Zhang, Chi, Hao Li, Kun Guo, et al.. (2021). DT-Loc: Monocular Visual Localization on HD Vector Map Using Distance Transforms of 2D Semantic Detections. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 1531–1538. 6 indexed citations
4.
Li, Xiangtai, Li Zhang, Guangliang Cheng, et al.. (2021). Global Aggregation Then Local Distribution for Scene Parsing. IEEE Transactions on Image Processing. 30. 6829–6842. 15 indexed citations
5.
Zhang, Chi, Liwen Liu, Kun Guo, et al.. (2021). Robust LiDAR Localization on an HD Vector Map without a Separate Localization Layer. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 5536–5543. 7 indexed citations
6.
Li, Xiangtai, et al.. (2019). Global Aggregation then Local Distribution in Fully Convolutional Networks.. arXiv (Cornell University). 244. 8 indexed citations
7.
Zhang, Li, Xiangtai Li, Anurag Arnab, et al.. (2019). Dual Graph Convolutional Network for Semantic Segmentation.. Oxford University Research Archive (ORA) (University of Oxford). 254. 23 indexed citations
8.
Shen, Yunhang, Rongrong Ji, Kuiyuan Yang, Cheng Deng, & Changhu Wang. (2019). Category-Aware Spatial Constraint for Weakly Supervised Detection. IEEE Transactions on Image Processing. 29. 843–858. 27 indexed citations
9.
Yu, Kun, et al.. (2018). DenseASPP for Semantic Segmentation in Street Scenes. 3684–3692. 1102 indexed citations breakdown →
10.
Yu, Wei, Xiaoshuai Sun, Kuiyuan Yang, Yong Rui, & Hongxun Yao. (2018). Hierarchical semantic image matching using CNN feature pyramid. Computer Vision and Image Understanding. 169. 40–51. 35 indexed citations
11.
Yu, Wei, Kuiyuan Yang, Hongxun Yao, Xiaoshuai Sun, & Pengfei Xu. (2016). Exploiting the complementary strengths of multi-layer CNN features for image retrieval. Neurocomputing. 237. 235–241. 106 indexed citations
12.
Zhang, Yanhao, et al.. (2016). From Seed Discovery to Deep Reconstruction. 72–76. 3 indexed citations
13.
Bai, Yalong, Wei Yu, Tianjun Xiao, et al.. (2014). Bag-of-Words Based Deep Neural Network for Image Retrieval. 229–232. 23 indexed citations
14.
Ma, Wei‐Ying, Tiejun Zhao, Kuiyuan Yang, Wei Yu, & Yalong Bai. (2013). Learning High-level Image Representation for Image Retrieval via Multi-Task DNN using Clickthrough Data. arXiv (Cornell University). 1 indexed citations
15.
Xu, Pengfei, Lei Zhang, Kuiyuan Yang, & Hongxun Yao. (2013). Nested-SIFT for Efficient Image Matching and Retrieval. IEEE Multimedia. 20(3). 34–46. 30 indexed citations
16.
Pan, Yingwei, Ting Yao, Kuiyuan Yang, et al.. (2013). Image search by graph-based label propagation with image representation from DNN. 397–400. 15 indexed citations
17.
Wang, Meng & Kuiyuan Yang. (2012). Constructing visual tag dictionary by mining community-contributed media corpus. Neurocomputing. 95. 3–10. 2 indexed citations
18.
Yang, Kuiyuan, Lei Zhang, Yong Rui, & Hao Zhang. (2012). PartBook for image parsing. 17–24. 2 indexed citations
19.
Yang, Kuiyuan, et al.. (2011). Semantic point detector. National University of Singapore. 1209–1212. 1 indexed citations
20.
Yang, Kuiyuan, et al.. (2011). Assemble New Object Detector With Few Examples. IEEE Transactions on Image Processing. 20(12). 3341–3349. 6 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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