Olga Veksler

49 papers receiving 7.3k citations

Hit Papers

Fast approximate energy minimization via graph cuts20012026200920172001200810002.0k3.0k4.0k

Peers

Olga Veksler
Comparison fields: 5 of 148
  • Computer Vision and Pattern Recognition 6.2k
  • Media Technology 1.1k
  • Aerospace Engineering 946
  • Artificial Intelligence 856
  • Computational Mechanics 546
Replace Roberto Manduchi with:
Roberto Manduchi United States
Chi–Keung Tang Hong Kong
Alexey Dosovitskiy Germany
Victor Lempitsky Russia
Tony Lindeberg Sweden
In So Kweon South Korea
Baba C. Vemuri United States
Vladimir Kolmogorov United Kingdom
Stefano Soatto United States
Ming-Yu Liu United States
Olga Veksler relative to Roberto Manduchi United States Roberto Manduchi's profile →
Citations per field
00.5×1.5×2.1×
Roberto Manduchi · 1×
Citations per year

Countries citing papers authored by Olga Veksler

Since Specialization
Citations

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

Fields of papers citing papers by Olga Veksler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olga Veksler

This figure shows the co-authorship network connecting the top 25 collaborators of Olga Veksler. A scholar is included among the top collaborators of Olga Veksler 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 Veksler. Olga Veksler 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 0
2 1
3 30
4 6
5 1
6 24
7
Minimizing Sparse High-Order Energies by Submodular Vertex-Cover
10
8 23
9 21
10 12
11 21
12
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priorsbreakdown →
643
13 20
14 54
15 42
16 247
17
Fast approximate energy minimization via graph cutsbreakdown →
4750
18
Efficient graph-based energy minimization methods in computer vision
150
19 302
20 112

About Olga Veksler

Olga Veksler is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 50 papers that have together received 7.7k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (25 papers), Advanced Vision and Imaging (19 papers) and Medical Image Segmentation Techniques (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (6.2k citations), Computer Graphics and Computer-Aided Design (536 citations) and Media Technology (1.1k citations). Olga Veksler has collaborated with scholars based in Canada, United States and France. Frequent co-authors include Ramin Zabih, Yuri Boykov, Rick Szeliski, Martha Tappen, Vladimir Kolmogorov, Carsten Rother, Daniel Scharstein, A. Agarwala, Lena Gorelick and Meng Tang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Medical Imaging and International Journal of Computer Vision.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026