Ivan Sipiran

1.8k total citations · 1 hit paper
45 papers, 1.0k citations indexed

About

Ivan Sipiran is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Geology. According to data from OpenAlex, Ivan Sipiran has authored 45 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Vision and Pattern Recognition, 22 papers in Computational Mechanics and 21 papers in Geology. Recurrent topics in Ivan Sipiran's work include Image Processing and 3D Reconstruction (22 papers), 3D Shape Modeling and Analysis (22 papers) and 3D Surveying and Cultural Heritage (21 papers). Ivan Sipiran is often cited by papers focused on Image Processing and 3D Reconstruction (22 papers), 3D Shape Modeling and Analysis (22 papers) and 3D Surveying and Cultural Heritage (21 papers). Ivan Sipiran collaborates with scholars based in Chile, Germany and Peru. Ivan Sipiran's co-authors include Benjamín Bustos, Tobias Schreck, Robert J. Gregor, Nancy Hitschfeld, José M. Saavedra, Γεώργιος Παπαϊωάννου, Afzal Godil, Ryutarou Ohbuchi, Dirk Smeets and Martin Reuter and has published in prestigious journals such as Communications of the ACM, Expert Systems with Applications and IEEE Access.

In The Last Decade

Ivan Sipiran

41 papers receiving 975 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.

Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes

2011 344 citations Ivan Sipiran, Benjamín Bustos The Visual Computer profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ivan Sipiran Chile	13	676	408	374	314	131	45	1.0k
Martin Bokeloh Germany	17	766 1.1×	611 1.5×	289 0.8×	199 0.6×	144 1.1×	29	1.2k
Patrick Labatut France	8	581 0.9×	204 0.5×	314 0.8×	255 0.8×	186 1.4×	11	817
Gaël Guennebaud France	15	583 0.9×	740 1.8×	295 0.8×	88 0.3×	189 1.4×	28	1.2k
Binh‐Son Hua Hong Kong	18	750 1.1×	836 2.0×	659 1.8×	272 0.9×	388 3.0×	40	1.5k
Gaël Guennebaud France	8	393 0.6×	562 1.4×	179 0.5×	70 0.2×	98 0.7×	16	897
Qiangui Huang United States	7	437 0.6×	537 1.3×	445 1.2×	122 0.4×	311 2.4×	9	949
Paul Guerrero United States	12	479 0.7×	517 1.3×	246 0.7×	75 0.2×	151 1.2×	37	879
Maxime Lhuillier France	19	1.3k 1.8×	74 0.2×	316 0.8×	865 2.8×	188 1.4×	44	1.5k
Joan Batlle Spain	8	1.0k 1.5×	114 0.3×	326 0.9×	200 0.6×	55 0.4×	13	1.2k
Yuchun Huang China	14	289 0.4×	387 0.9×	424 1.1×	102 0.3×	356 2.7×	47	1.0k

Countries citing papers authored by Ivan Sipiran

Since Specialization

Citations

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

Fields of papers citing papers by Ivan Sipiran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Sipiran

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

20 of 20 papers shown

1.

Sipiran, Ivan. (2025). Symmetry Shape Analysis. 1–6. 1 indexed citations

2.

Sipiran, Ivan, et al.. (2025). SHREC 2025: Partial retrieval benchmark. Computers & Graphics. 132. 104397–104397. 1 indexed citations

3.

Bustos, Benjamín, et al.. (2024). Multi-label learning on low label density sets with few examples. Expert Systems with Applications. 265. 125942–125942.

4.

Sipiran, Ivan. (2024). The Role of Computing in the Study of Latin American Cultural Heritage. Communications of the ACM. 67(8). 58–62. 1 indexed citations

5.

Bustos, Benjamín, et al.. (2023). A convolutional architecture for 3D model embedding using image views. The Visual Computer. 40(3). 1601–1615. 2 indexed citations

6.

Sipiran, Ivan, et al.. (2023). Visual Exploration of Repetitive Patterns on Ancient Peruvian Pottery. Digital Library (University of West Bohemia). 31(1-2). 25–33.

7.

Hitschfeld, Nancy, et al.. (2023). Large-scale multi-unit floor plan dataset for architectural plan analysis and recognition. Automation in Construction. 156. 105132–105132. 10 indexed citations

8.

Biasotti, Silvia, Bianca Falcidieno, Κωνσταντίνος Μουστάκας, et al.. (2022). SHREC 2022: Fitting and recognition of simple geometric primitives on point clouds. Computers & Graphics. 107. 32–49. 6 indexed citations

9.

Sipiran, Ivan, et al.. (2022). Interactive annotation of geometric ornamentation on painted pottery assisted by deep learning. it - Information Technology. 64(6). 217–231. 1 indexed citations

10.

Bustos, Benjamín, et al.. (2022). A comprehensive review of the video-to-text problem. Artificial Intelligence Review. 55(5). 4165–4239.

11.

Sipiran, Ivan, et al.. (2022). Data-Driven Restoration of Digital Archaeological Pottery with Point Cloud Analysis. International Journal of Computer Vision. 130(9). 2149–2165. 15 indexed citations

12.

Sipiran, Ivan. (2018). Completion of Cultural Heritage Objects with Rotational Symmetry. Eurographics. 2 indexed citations

13.

Behrisch, Michael, et al.. (2016). Guiding the exploration of scatter plot data using motif-based interest measures. Journal of Visual Languages & Computing. 36. 1–12. 15 indexed citations

14.

Sipiran, Ivan, Jakub Lokoč, Benjamín Bustos, & Tomáš Skopal. (2016). Scalable 3D shape retrieval using local features and the signature quadratic form distance. The Visual Computer. 33(12). 1571–1585. 6 indexed citations

15.

Behrisch, Michael, et al.. (2015). Guiding the Exploration of Scatter Plot Data Using Motif-Based Interest Measures. 1–8. 6 indexed citations

16.

Sipiran, Ivan, Benjamín Bustos, Tobias Schreck, et al.. (2015). Scalability of Non-Rigid 3D Shape Retrieval. Eurographics. 6 indexed citations

17.

Sipiran, Ivan & Benjamín Bustos. (2013). A Fully Hierarchical Approach for Finding Correspondences in Non-rigid Shapes. 28. 817–824. 3 indexed citations

18.

Sipiran, Ivan, Benjamín Bustos, & Tobias Schreck. (2013). Data-aware 3D partitioning for generic shape retrieval. Computers & Graphics. 37(5). 460–472. 16 indexed citations

19.

Sipiran, Ivan, et al.. (2013). SHREC'13 Track: Large-Scale Partial Shape Retrieval Using Simulated Range Images. KOPS (University of Konstanz). 12 indexed citations

20.

Biasotti, Silvia, Xiao Bai, Benjamín Bustos, et al.. (2012). SHREC'12 Track: Stability on Abstract Shapes. ISTI Open Portal. 101–107. 11 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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