Olga Sorkine

76 papers receiving 5.8k citations

Hit Papers

Optimized scale-and-stretch for image resizing200720262013201920082007100200300400

Peers

Olga Sorkine
Comparison fields: 5 of 116
  • Computer Vision and Pattern Recognition 3.7k
  • Computational Mechanics 3.1k
  • Computer Graphics and Computer-Aided Design 2.7k
  • Control and Systems Engineering 757
  • Media Technology 327
Replace Chiew‐Lan Tai with:
Chiew‐Lan Tai Hong Kong
Li‐Yi Wei United States
Tien‐Tsin Wong Hong Kong
Jingyi Yu China
Yebin Liu China
Tong‐Yee Lee Taiwan
Angjoo Kanazawa United States
Evangelos Kalogerakis United States
Wolfgang Straßer Germany
Jiajun Wu United States
Olga Sorkine relative to Chiew‐Lan Tai Hong Kong Chiew‐Lan Tai's profile →
Citations per field
00.5×1.5×2.3×
Chiew‐Lan Tai · 1×
Citations per year

Countries citing papers authored by Olga Sorkine

Since Specialization
Citations

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

Fields of papers citing papers by Olga Sorkine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olga Sorkine

This figure shows the co-authorship network connecting the top 25 collaborators of Olga Sorkine. A scholar is included among the top collaborators of Olga Sorkine 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 Olga Sorkine. Olga Sorkine 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
#WorkIndexed citations
1
Course: Modern Approaches to Media Retargeting
1
2 2
3 8
4 30
5 40
6 34
7 100
8 34
9 176
10 8
11
Sketch Based Image Deformation.
22
12
On Linear Variational Surface Deformation Methodsbreakdown →
435
13 0
14 229
15 241
16 48
17 19
18 128
19 11
20 32

About Olga Sorkine

Olga Sorkine is a scholar working on Computer Graphics and Computer-Aided Design, Computational Mechanics and Computer Vision and Pattern Recognition, having authored 78 papers that have together received 6.0k indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (43 papers), Computer Graphics and Visualization Techniques (40 papers) and Advanced Vision and Imaging (15 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (2.7k citations), Computer Vision and Pattern Recognition (3.7k citations) and Computational Mechanics (3.1k citations). Olga Sorkine has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Daniel Cohen‐Or, Andrew Nealen, Mario Botsch, Marc Alexa, Tong‐Yee Lee, Ariel Shamir, Yu-Shuen Wang, Alec Jacobson, Diego Gutiérrez and Yuki Igarashi. Their work appears in journals such as ACM Transactions on Graphics, IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum.

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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