Yan‐Pei Cao

2.2k total citations · 2 hit papers
57 papers, 1.1k citations indexed

About

Yan‐Pei Cao is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Yan‐Pei Cao has authored 57 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computer Vision and Pattern Recognition, 34 papers in Computational Mechanics and 29 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Yan‐Pei Cao's work include 3D Shape Modeling and Analysis (34 papers), Computer Graphics and Visualization Techniques (29 papers) and Advanced Vision and Imaging (27 papers). Yan‐Pei Cao is often cited by papers focused on 3D Shape Modeling and Analysis (34 papers), Computer Graphics and Visualization Techniques (29 papers) and Advanced Vision and Imaging (27 papers). Yan‐Pei Cao collaborates with scholars based in China, Hong Kong and United States. Yan‐Pei Cao's co-authors include Pengfei Wan, Zhizhong Han, Wen Zheng, Xin Wen, Yu-Shen Liu, Ying Shan, Xiang Peng, Shi‐Min Hu, Leif Kobbelt and Lin Gao and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Yan‐Pei Cao

47 papers receiving 1.0k citations

Hit Papers

SnowflakeNet: Point Cloud Completion by Snowflake Point D... 2021 2026 2022 2024 2021 2024 50 100 150
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. SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
    2021 171 citations Xin Wen, Yu-Shen Liu et al. profile →
  2. Recent advances in 3D Gaussian splatting
    2024 65 citations Yan‐Pei Cao et al. profile →

Peers

Yan‐Pei Cao
Paul Guerrero United States
Ruihui Li China
Maxim Tatarchenko Germany
Martin Bokeloh Germany
Wentao Yuan United States
Gaël Guennebaud France
Gernot Riegler Austria
Minhyuk Sung South Korea
Pengfei Wan China
Ali Osman Ulusoy Germany
Paul Guerrero United States
Yan‐Pei Cao
Citations per year, relative to Yan‐Pei Cao Yan‐Pei Cao (= 1×) peers Paul Guerrero

Countries citing papers authored by Yan‐Pei Cao

Since Specialization
Citations

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

Fields of papers citing papers by Yan‐Pei Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yan‐Pei Cao. 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 Yan‐Pei Cao. The network helps show where Yan‐Pei Cao may publish in the future.

Co-authorship network of co-authors of Yan‐Pei Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Yan‐Pei Cao. A scholar is included among the top collaborators of Yan‐Pei Cao 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 Yan‐Pei Cao. Yan‐Pei Cao 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.
2.
Li, Yangguang, Zexiang Liu, Yuan Liang, et al.. (2025). TripoSG: High-Fidelity 3D Shape Synthesis Using Large-Scale Rectified Flow Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. PP. 1–18.
3.
Guo, Meng-Hao, et al.. (2025). One Model to Rig Them All: Diverse Skeleton Rigging with UniRig. ACM Transactions on Graphics. 44(4). 1–18.
4.
Zhang, Jingbo, Xiaoyu Li, Qi Zhang, et al.. (2025). HumanRef-GS: Image-to-3D Human Generation With Reference-Guided Diffusion and 3D Gaussian Splatting. IEEE Transactions on Circuits and Systems for Video Technology. 35(7). 6867–6880. 2 indexed citations
5.
Zhang, Xiao, et al.. (2025). Comprehensive Analysis of m6A‐Related Programmed Cell Death Genes Unveils a Novel Prognostic Model for Lung Adenocarcinoma. Journal of Cellular and Molecular Medicine. 29(2). e70255–e70255. 1 indexed citations
6.
7.
Lyu, Xiaoyang, et al.. (2025). Deformable Radial Kernel Splatting. 21513–21523.
8.
Sun, Jingxiang, Cheng Peng, Ruizhi Shao, et al.. (2025). DreamCraft3D++: Efficient Hierarchical 3D Generation with Multi-Plane Reconstruction Model. IEEE Transactions on Pattern Analysis and Machine Intelligence. PP. 1–15.
9.
Zhang, Xiao, Jiatao Liu, Yan‐Pei Cao, et al.. (2025). Multi-omic and machine learning analysis of mitochondrial RNA modification genes in lung adenocarcinoma for prognostic and therapeutic implications. Translational Oncology. 53. 102306–102306. 1 indexed citations
10.
Cao, Yan‐Pei, et al.. (2024). SparseGNV: Generating Novel Views of Indoor Scenes with Sparse RGB-D Images. Proceedings of the AAAI Conference on Artificial Intelligence. 38(2). 1308–1316. 1 indexed citations
11.
Guo, Meng-Hao, et al.. (2024). CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization. ACM Transactions on Graphics. 43(4). 1–13. 5 indexed citations
12.
Cao, Yan‐Pei, et al.. (2024). GP-Recon: Online Monocular Neural 3D Reconstruction With Geometric Prior. IEEE Transactions on Visualization and Computer Graphics. 31(9). 4790–4804.
13.
Li, Xiaoyu, et al.. (2024). ConTex-Human: Free-View Rendering of Human from a Single Image with Texture-Consistent Synthesis. 10084–10094. 6 indexed citations
14.
Zhang, Jingbo, et al.. (2024). HumanRef: Single Image to 3D Human Generation via Reference-Guided Diffusion. 1844–1854. 5 indexed citations
15.
Cao, Yan‐Pei, et al.. (2024). DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models. 958–968. 39 indexed citations
16.
Liu, Xinhai, et al.. (2023). D-Net: Learning for distinctive point clouds by self-attentive point searching and learnable feature fusion. Computer Aided Geometric Design. 104. 102206–102206. 1 indexed citations
17.
Guo, Yuan-Chen, Yan‐Pei Cao, Chen Wang, et al.. (2023). VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthesis. 1–11. 9 indexed citations
18.
Fan, Yanbo, Yong Zhang, Yunpeng Bai, et al.. (2023). NOFA: NeRF-based One-shot Facial Avatar Reconstruction. 1–12. 14 indexed citations
19.
Peng, Xiang, Xin Wen, Yu-Shen Liu, et al.. (2022). Snowflake Point Deconvolution for Point Cloud Completion and Generation with Skip-Transformer. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(5). 1–18. 48 indexed citations
20.
Yang, Sheng, Zhen Liu, Yan‐Pei Cao, et al.. (2022). Meiosis resumption in human primordial germ cells from induced pluripotent stem cells by in vitro activation and reconstruction of ovarian nests. Stem Cell Research & Therapy. 13(1). 339–339. 14 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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