Jinlong Yang

961 total citations · 1 hit paper
6 papers, 413 citations indexed

About

Jinlong Yang is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Jinlong Yang has authored 6 papers receiving a total of 413 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Computational Mechanics and 3 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Jinlong Yang's work include 3D Shape Modeling and Analysis (5 papers), Human Pose and Action Recognition (3 papers) and Computer Graphics and Visualization Techniques (3 papers). Jinlong Yang is often cited by papers focused on 3D Shape Modeling and Analysis (5 papers), Human Pose and Action Recognition (3 papers) and Computer Graphics and Visualization Techniques (3 papers). Jinlong Yang collaborates with scholars based in Germany, Switzerland and China. Jinlong Yang's co-authors include Qianli Ma, Michael J. Black, Siyu Tang, Shunsuke Saito, Anurag Ranjan, Sergi Pujades, Gerard Pons‐Moll, Weiyi Hou, Bin Zhang and Xingchen Ye and has published in prestigious journals such as Small, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and SPIRE - Sciences Po Institutional REpository.

In The Last Decade

Jinlong Yang

5 papers receiving 396 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.

Learning to Dress 3D People in Generative Clothing

2020 205 citations Qianli Ma, Jinlong Yang et al. SPIRE - Sciences Po Institutional REpository profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jinlong Yang Germany	4	344	306	190	72	15	6	413
Guanying Chen China	11	103 0.3×	286 0.9×	135 0.7×	17 0.2×	20 1.3×	20	370
Binh Huy Le United States	9	238 0.7×	171 0.6×	121 0.6×	131 1.8×	5 0.3×	14	315
Tsuneya Kurihara Japan	8	308 0.9×	189 0.6×	273 1.4×	228 3.2×	31 2.1×	14	483
Michael Hauth Germany	7	204 0.6×	47 0.2×	186 1.0×	45 0.6×	21 1.4×	10	271
Igor Santesteban Spain	5	265 0.8×	150 0.5×	194 1.0×	79 1.1×	2 0.1×	8	306
Weihua Tong China	8	377 1.1×	59 0.2×	175 0.9×	7 0.1×	10 0.7×	10	400
Henrik Zimmer Germany	5	372 1.1×	80 0.3×	379 2.0×	13 0.2×	9 0.6×	7	481
Tingbo Hou United States	10	80 0.2×	132 0.4×	33 0.2×	9 0.1×	40 2.7×	32	303
Mamoru Hosaka Japan	10	196 0.6×	56 0.2×	141 0.7×	14 0.2×	18 1.2×	22	280
Henrik Weimer United States	6	309 0.9×	55 0.2×	170 0.9×	27 0.4×	17 1.1×	10	349

Countries citing papers authored by Jinlong Yang

Since Specialization

Citations

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

Fields of papers citing papers by Jinlong Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinlong Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Jinlong Yang. A scholar is included among the top collaborators of Jinlong 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 Jinlong Yang. Jinlong Yang 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:

6 of 6 papers shown

1.

Sanyal, Soubhik, Partha S. Ghosh, Jinlong Yang, et al.. (2024). SCULPT: Shape-Conditioned Unpaired Learning of Pose-dependent Clothed and Textured Human Meshes. 2362–2371. 1 indexed citations

2.

Wu, Chenglei, et al.. (2024). FabricDiffusion: High-Fidelity Texture Transfer for 3D Garments Generation from In-The-Wild Images. 1–12.

3.

Saito, Shunsuke, Jinlong Yang, Qianli Ma, & Michael J. Black. (2021). SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks. 2885–2896. 133 indexed citations

4.

Ma, Qianli, Jinlong Yang, Siyu Tang, & Michael J. Black. (2021). The Power of Points for Modeling Humans in Clothing. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 10954–10964. 61 indexed citations

5.

Ma, Qianli, Jinlong Yang, Anurag Ranjan, et al.. (2020). Learning to Dress 3D People in Generative Clothing. SPIRE - Sciences Po Institutional REpository. 6468–6477. 205 indexed citations breakdown →

6.

Zhang, Bin, Weiyi Hou, Xi Zhu, et al.. (2006). Multiarmed Tubular Selenium with Potentially Unique Electrical Properties: Solution‐Phase Synthesis and First‐Principles Calculation. Small. 3(1). 101–105. 13 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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