Chenyang Si

6.4k total citations · 3 hit papers
34 papers, 1.7k citations indexed

About

Chenyang Si is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Chenyang Si has authored 34 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 11 papers in Molecular Biology and 6 papers in Artificial Intelligence. Recurrent topics in Chenyang Si's work include Human Pose and Action Recognition (7 papers), CRISPR and Genetic Engineering (7 papers) and Multimodal Machine Learning Applications (7 papers). Chenyang Si is often cited by papers focused on Human Pose and Action Recognition (7 papers), CRISPR and Genetic Engineering (7 papers) and Multimodal Machine Learning Applications (7 papers). Chenyang Si collaborates with scholars based in China, Singapore and United States. Chenyang Si's co-authors include Yichen Zhou, Weihao Yu, Xinchao Wang, Mi Luo, Pan Zhou, Jiashi Feng, Shuicheng Yan, Liang Wang, Weizhi Ji and Yu Kang and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and Biomaterials.

In The Last Decade

Chenyang Si

32 papers receiving 1.6k citations

Hit Papers

MetaFormer is Actually What You Need for Vision 2022 2026 2023 2024 2022 2024 2024 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chenyang Si China 15 838 381 305 163 154 34 1.7k
Xiaoming Wei China 21 806 1.0× 386 1.0× 302 1.0× 161 1.0× 97 0.6× 82 2.1k
Lin Gu Japan 24 921 1.1× 392 1.0× 506 1.7× 211 1.3× 367 2.4× 83 2.5k
Jagath Samarabandu Canada 23 558 0.7× 473 1.2× 528 1.7× 137 0.8× 103 0.7× 114 2.2k
Xiaohong Jia China 16 615 0.7× 317 0.8× 318 1.0× 157 1.0× 373 2.4× 39 1.8k
Jonas Mueller United States 11 452 0.5× 231 0.6× 687 2.3× 77 0.5× 95 0.6× 21 1.7k
Shishir K. Shah United States 24 1.8k 2.1× 148 0.4× 300 1.0× 280 1.7× 174 1.1× 151 2.3k
Joan Serrat Spain 20 929 1.1× 543 1.4× 123 0.4× 52 0.3× 168 1.1× 71 1.8k
Óscar Déniz Spain 23 1.4k 1.6× 142 0.4× 891 2.9× 153 0.9× 218 1.4× 112 2.4k
Christian Rupprecht Germany 22 841 1.0× 116 0.3× 239 0.8× 144 0.9× 49 0.3× 77 1.7k
Hélio Pedrini Brazil 25 1.8k 2.2× 60 0.2× 461 1.5× 150 0.9× 325 2.1× 200 2.7k

Countries citing papers authored by Chenyang Si

Since Specialization
Citations

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

Fields of papers citing papers by Chenyang Si

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chenyang Si

This figure shows the co-authorship network connecting the top 25 collaborators of Chenyang Si. A scholar is included among the top collaborators of Chenyang Si 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 Chenyang Si. Chenyang Si 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, Peng, Zhiyang Dou, Chenyang Si, et al.. (2025). Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video Generation Control. DR-NTU (Nanyang Technological University). 1–12.
2.
Si, Chenyang, et al.. (2024). Federated zero-shot learning with mid-level semantic knowledge transfer. Pattern Recognition. 156. 110824–110824. 6 indexed citations
3.
Jiang, Yuming, Tianxing Wu, Chenyang Si, et al.. (2024). VideoBooth: Diffusion-based Video Generation with Image Prompts. 6689–6700. 13 indexed citations
4.
Si, Chenyang, Shangchen Zhou, Jiangning Zhang, et al.. (2024). Towards Language-Driven Video Inpainting via Multimodal Large Language Models. 12501–12511. 7 indexed citations
5.
Si, Chenyang, Ziqi Huang, Yuming Jiang, & Ziwei Liu. (2024). FreeU: Free Lunch in Diffusion U-Net. 4733–4743. 50 indexed citations breakdown →
6.
Chen, Wentao, Chenyang Si, Zhang Zhang, et al.. (2023). Notice of Removal: Semantic Prompt for Few-Shot Image Recognition. 1–1. 3 indexed citations
7.
Zhu, Xiaoqing, Yicheng Guo, Kui Duan, et al.. (2022). BRN2 as a key gene drives the early primate telencephalon development. Science Advances. 8(9). eabl7263–eabl7263. 7 indexed citations
8.
Si, Chenyang. (2022). Inception Transformer. arXiv (Cornell University). 23495–23509.
9.
Duan, Kui, Chenyang Si, Shumei Zhao, et al.. (2021). The Long Terminal Repeats of ERV6 Are Activated in Pre-Implantation Embryos of Cynomolgus Monkey. Cells. 10(10). 2710–2710. 2 indexed citations
10.
Yang, Ran, Alexander Goedel, Yu Kang, et al.. (2021). Amnion signals are essential for mesoderm formation in primates. Nature Communications. 12(1). 73 indexed citations
11.
Chu, Chu, Wenhao Zhang, Yu Kang, et al.. (2021). Analysis of developmental imprinting dynamics in primates using SNP-free methods to identify imprinting defects in cloned placenta. Developmental Cell. 56(20). 2826–2840.e7. 14 indexed citations
12.
Wang, Fang, Weiqi Zhang, Qiaoyan Yang, et al.. (2020). Generation of a Hutchinson–Gilford progeria syndrome monkey model by base editing. Protein & Cell. 11(11). 809–824. 51 indexed citations
13.
Si, Chenyang, Ya Jing, Wei Wang, Liang Wang, & Tieniu Tan. (2020). Skeleton-based action recognition with hierarchical spatial reasoning and temporal stack learning network. Pattern Recognition. 107. 107511–107511. 67 indexed citations
14.
Chu, Chu, Zhaohui Yang, Jiayin Yang, et al.. (2019). Homologous recombination-mediated targeted integration in monkey embryos using TALE nucleases. BMC Biotechnology. 19(1). 7–7. 9 indexed citations
15.
Jing, Ya, Chenyang Si, Junbo Wang, et al.. (2018). Pose-Guided Joint Global and Attentive Local Matching Network for Text-Based Person Search. arXiv (Cornell University). 8 indexed citations
16.
Jing, Ya, Chenyang Si, Junbo Wang, et al.. (2018). Cascade Attention Network for Person Search: Both Image and Text-Image Similarity Selection.. arXiv (Cornell University). 5 indexed citations
17.
Si, Chenyang, Wei Wang, Liang Wang, & Tieniu Tan. (2018). Multistage Adversarial Losses for Pose-Based Human Image Synthesis. 118–126. 36 indexed citations
18.
Gao, Fei, Yuyu Niu, Yi Eve Sun, et al.. (2017). De novo DNA methylation during monkey pre-implantation embryogenesis. Cell Research. 27(4). 526–539. 35 indexed citations
19.
Chen, Yongchang, Yinghui Zheng, Yu Kang, et al.. (2015). Functional disruption of the dystrophin gene in rhesus monkey using CRISPR/Cas9. Human Molecular Genetics. 24(13). 3764–3774. 180 indexed citations
20.
Wang, Hong, Tao Tan, Junfeng Wang, et al.. (2015). Rhesus monkey model of liver disease reflecting clinical disease progression and hepatic gene expression analysis. Scientific Reports. 5(1). 15019–15019. 15 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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