Zhixin Shu

2.1k total citations · 1 hit paper
27 papers, 963 citations indexed

About

Zhixin Shu is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics. According to data from OpenAlex, Zhixin Shu has authored 27 papers receiving a total of 963 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 9 papers in Computer Graphics and Computer-Aided Design and 4 papers in Computational Mechanics. Recurrent topics in Zhixin Shu's work include Advanced Vision and Imaging (11 papers), Computer Graphics and Visualization Techniques (9 papers) and Generative Adversarial Networks and Image Synthesis (7 papers). Zhixin Shu is often cited by papers focused on Advanced Vision and Imaging (11 papers), Computer Graphics and Visualization Techniques (9 papers) and Generative Adversarial Networks and Image Synthesis (7 papers). Zhixin Shu collaborates with scholars based in United States, France and Germany. Zhixin Shu's co-authors include Kalyan Sunkavalli, Dimitris Samaras, Eli Shechtman, Zexiang Xu, Sunil Hadap, Sai Bi, Qiangeng Xu, Julien Philip, Ulrich Neumann and Ersin Yumer and has published in prestigious journals such as ACM Transactions on Graphics, Biochemical Society Transactions and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Zhixin Shu

23 papers receiving 920 citations

Hit Papers

Point-NeRF: Point-based Neural Radiance Fields 2022 2026 2023 2024 2022 100 200 300
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. Point-NeRF: Point-based Neural Radiance Fields
    2022 322 citations Qiangeng Xu, Zexiang Xu et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhixin Shu United States 13 824 335 282 62 59 27 963
Vickie Ye United States 5 755 0.9× 447 1.3× 335 1.2× 97 1.6× 71 1.2× 6 892
Zhengqi Li United States 12 774 0.9× 347 1.0× 231 0.8× 123 2.0× 50 0.8× 20 920
Abhishek Kar United States 10 876 1.1× 442 1.3× 326 1.2× 130 2.1× 92 1.6× 12 988
Richard Tucker United States 10 1.0k 1.2× 558 1.7× 247 0.9× 93 1.5× 49 0.8× 16 1.1k
Eric R. Chan United States 7 677 0.8× 410 1.2× 376 1.3× 44 0.7× 40 0.7× 8 858
Julien Philip United States 9 698 0.8× 526 1.6× 316 1.1× 83 1.3× 72 1.2× 14 835
Zhouhui Lian China 20 1.1k 1.4× 368 1.1× 458 1.6× 79 1.3× 112 1.9× 83 1.4k
Stephan R. Richter Germany 11 425 0.5× 154 0.5× 244 0.9× 69 1.1× 114 1.9× 19 643
Kangxue Yin Canada 12 467 0.6× 361 1.1× 363 1.3× 54 0.9× 75 1.3× 16 725
Haggai Maron Israel 7 441 0.5× 183 0.5× 280 1.0× 71 1.1× 99 1.7× 16 670

Countries citing papers authored by Zhixin Shu

Since Specialization
Citations

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

Fields of papers citing papers by Zhixin Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhixin Shu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhixin Shu. A scholar is included among the top collaborators of Zhixin Shu 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 Zhixin Shu. Zhixin Shu 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.
Athar, ShahRukh, et al.. (2025). Rig3DGS: Creating Controllable Portraits From Casual Monocular Videos. 1541–1550.
3.
Yoon, Jae Shin, et al.. (2024). Generative Portrait Shadow Removal. ACM Transactions on Graphics. 43(6). 1–13.
4.
Shu, Zhixin, et al.. (2024). Digital Salon: An AI and Physics-Driven Tool for 3D Hair Grooming and Simulation. 1–1. 1 indexed citations
5.
Tan, Hao, Zhixin Shu, Yi Zhou, et al.. (2024). Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning. 6369–6379. 1 indexed citations
6.
Mei, Yiqun, et al.. (2024). Holo-Relighting: Controllable Volumetric Portrait Relighting from a Single Image. 4263–4273. 3 indexed citations
7.
Shu, Zhixin, et al.. (2024). In-N-Out: Faithful 3D GAN Inversion with Volumetric Decomposition for Face Editing. 7225–7235. 2 indexed citations
8.
Xiong, Wei, et al.. (2024). Relightful Harmonization: Lighting-Aware Portrait Background Replacement. 6452–6462. 7 indexed citations
9.
Kuang, Zhengfei, Fujun Luan, Sai Bi, et al.. (2023). PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fields. 20691–20700. 26 indexed citations
10.
Hold-Geoffroy, Yannick, et al.. (2022). Temporally Consistent Relighting for Portrait Videos. 719–728. 4 indexed citations
11.
Xu, Qiangeng, Zexiang Xu, Julien Philip, et al.. (2022). Point-NeRF: Point-based Neural Radiance Fields. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 5428–5438. 322 indexed citations breakdown →
12.
Ma, Ke, et al.. (2022). Learning From Documents in the Wild to Improve Document Unwarping. 1–9. 19 indexed citations
13.
Yoon, Jae Shin, Duygu Ceylan, Jingwan Lu, et al.. (2022). Learning Motion-Dependent Appearance for High-Fidelity Rendering of Dynamic Humans from a Single Camera. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 3397–3407. 7 indexed citations
14.
Athar, ShahRukh, Zexiang Xu, Kalyan Sunkavalli, Eli Shechtman, & Zhixin Shu. (2022). RigNeRF: Fully Controllable Neural 3D Portraits. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 20332–20341. 71 indexed citations
15.
Liu, Yuchen, Zhixin Shu, Yijun Li, et al.. (2021). Content-Aware GAN Compression. 12151–12161. 29 indexed citations
16.
Shu, Zhixin, Ersin Yumer, Sunil Hadap, et al.. (2017). Neural Face Editing with Intrinsic Image Disentangling. 5444–5453. 167 indexed citations
17.
Shu, Zhixin, Sunil Hadap, Eli Shechtman, et al.. (2017). Portrait lighting transfer using a mass transport approach. ACM Transactions on Graphics. 36(4). 1–1. 23 indexed citations
18.
Shu, Zhixin, Sunil Hadap, Eli Shechtman, et al.. (2017). Portrait Lighting Transfer Using a Mass Transport Approach. ACM Transactions on Graphics. 36(4). 1–1. 33 indexed citations
19.
Shu, Zhixin, Eli Shechtman, Dimitris Samaras, & Sunil Hadap. (2016). EyeOpener. ACM Transactions on Graphics. 36(1). 1–13. 43 indexed citations
20.
Albery, W. John, et al.. (1986). Direct electrochemical studies of ligand-binding reactions to cytochrome c oxidase. Biochemical Society Transactions. 14(6). 1212–1213. 5 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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