Simone Melzi

2.9k total citations
37 papers, 874 citations indexed

About

Simone Melzi is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Simone Melzi has authored 37 papers receiving a total of 874 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computational Mechanics, 23 papers in Computer Vision and Pattern Recognition and 15 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Simone Melzi's work include 3D Shape Modeling and Analysis (24 papers), Computer Graphics and Visualization Techniques (15 papers) and Advanced Numerical Analysis Techniques (8 papers). Simone Melzi is often cited by papers focused on 3D Shape Modeling and Analysis (24 papers), Computer Graphics and Visualization Techniques (15 papers) and Advanced Numerical Analysis Techniques (8 papers). Simone Melzi collaborates with scholars based in Italy, France and United Kingdom. Simone Melzi's co-authors include Giorgio Roffo, Marco Cristani, Umberto Castellani, Michael M. Bronstein, Maks Ovsjanikov, Emanuele Rodolà, Peter Wonka, Alessandro Vinciarelli, Jing Ren and Jonathan Masci and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and International Journal of Computer Vision.

In The Last Decade

Simone Melzi

34 papers receiving 846 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simone Melzi Italy 14 449 413 209 178 65 37 874
Ali Thabet Saudi Arabia 13 709 1.6× 348 0.8× 643 3.1× 129 0.7× 250 3.8× 26 1.6k
Pere‐Pau Vázquez Spain 15 633 1.4× 134 0.3× 59 0.3× 303 1.7× 48 0.7× 78 884
Lee M. Seversky United States 9 227 0.5× 219 0.5× 62 0.3× 146 0.8× 148 2.3× 16 575
Bo Dai China 21 1.7k 3.8× 186 0.5× 768 3.7× 128 0.7× 74 1.1× 55 2.2k
Hao Zhao China 15 486 1.1× 80 0.2× 143 0.7× 58 0.3× 69 1.1× 47 768
Qiming Hou China 12 670 1.5× 317 0.8× 82 0.4× 419 2.4× 29 0.4× 24 1.0k
Feng Dai China 17 1.4k 3.1× 281 0.7× 249 1.2× 26 0.1× 17 0.3× 60 1.8k
Mathieu Aubry France 14 1.1k 2.4× 603 1.5× 172 0.8× 303 1.7× 184 2.8× 30 1.6k
M.G. Strintzis Greece 16 573 1.3× 98 0.2× 197 0.9× 25 0.1× 49 0.8× 72 1.1k
Yibing Zhan China 22 1.0k 2.2× 119 0.3× 628 3.0× 33 0.2× 82 1.3× 105 1.6k

Countries citing papers authored by Simone Melzi

Since Specialization
Citations

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

Fields of papers citing papers by Simone Melzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone Melzi

This figure shows the co-authorship network connecting the top 25 collaborators of Simone Melzi. A scholar is included among the top collaborators of Simone Melzi 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 Simone Melzi. Simone Melzi 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.
Melzi, Simone, et al.. (2024). Deformation Recovery: Localized Learning for Detail-Preserving Deformations. ACM Transactions on Graphics. 43(6). 1–16. 1 indexed citations
2.
Squarcina, Letizia, et al.. (2024). Fetal gestational age prediction via shape descriptors of cortical development. Frontiers in Pediatrics. 12. 1471080–1471080.
3.
Raganato, Alessandro, Gabriella Pasi, & Simone Melzi. (2023). Attention And Positional Encoding Are (Almost) All You Need For Shape Matching. Computer Graphics Forum. 42(5). 3 indexed citations
4.
Taverne, M.A.M., et al.. (2023). Assessing craniofacial growth and form without landmarks: A new automatic approach based on spectral methods. Journal of Morphology. 284(8). e21609–e21609. 2 indexed citations
5.
Melzi, Simone, et al.. (2023). GIM3D plus: A labeled 3D dataset to design data-driven solutions for dressed humans. Graphical Models. 129. 101187–101187. 4 indexed citations
6.
Marin, Riccardo, et al.. (2021). A functional skeleton transfer. BOA (University of Milano-Bicocca).
7.
Cosmo, Luca, et al.. (2021). Universal Spectral Adversarial Attacks for Deformable Shapes. ARCA (Università Ca' Foscari Venezia). 7 indexed citations
8.
Marin, Riccardo, et al.. (2021). Spectral Shape Recovery and Analysis Via Data-driven Connections. International Journal of Computer Vision. 129(10). 2745–2760. 10 indexed citations
9.
Ren, Jing, Simone Melzi, Peter Wonka, & Maks Ovsjanikov. (2021). Discrete Optimization for Shape Matching. Computer Graphics Forum. 40(5). 81–96. 23 indexed citations
10.
Marin, Riccardo, Simone Melzi, Emanuele Rodolà, & Umberto Castellani. (2020). FARM: Functional Automatic Registration Method for 3D Human Bodies. BOA (University of Milano-Bicocca). 35 indexed citations
11.
Roffo, Giorgio, Simone Melzi, Umberto Castellani, Alessandro Vinciarelli, & Marco Cristani. (2020). Infinite Feature Selection: A Graph-based Feature Filtering Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(12). 4396–4410. 136 indexed citations
12.
Marin, Riccardo, et al.. (2020). Instant recovery of shape from spectrum via latent space connections. arXiv (Cornell University).
13.
Lai, Yu‐Kun, Paul L. Rosin, Stefano Zappalá, et al.. (2020). SHREC’20: Shape correspondence with non-isometric deformations. Computers & Graphics. 92. 28–43. 24 indexed citations
14.
Marin, Riccardo, Simone Melzi, Emanuele Rodolà, & Umberto Castellani. (2019). High-Resolution Augmentation for Automatic Template-Based Matching of Human Models. BOA (University of Milano-Bicocca). 230–239. 2 indexed citations
15.
Melzi, Simone, Maks Ovsjanikov, Giorgio Roffo, Marco Cristani, & Umberto Castellani. (2018). Discrete Time Evolution Process Descriptor for Shape Analysis and Matching. ACM Transactions on Graphics. 37(1). 1–18. 14 indexed citations
16.
Melzi, Simone, et al.. (2018). Improved Functional Mappings via Product Preservation. Computer Graphics Forum. 37(2). 179–190. 28 indexed citations
17.
Roffo, Giorgio & Simone Melzi. (2017). Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 19–35. 7 indexed citations
18.
Roffo, Giorgio & Simone Melzi. (2016). Feature Selection via Eigenvector Centrality. 1–12. 10 indexed citations
19.
Boscaini, Davide, Jonathan Masci, Simone Melzi, et al.. (2015). Learning class‐specific descriptors for deformable shapes using localized spectral convolutional networks. Computer Graphics Forum. 34(5). 13–23. 124 indexed citations
20.
Roffo, Giorgio, Simone Melzi, & Marco Cristani. (2015). Infinite Feature Selection. BOA (University of Milano-Bicocca). 4202–4210. 221 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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