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.
Robust wide-baseline stereo from maximally stable extremal regions
20042.5k citationsJiřı́ Matas, Ondřej Chum et al.profile →
This map shows the geographic impact of Tomáš Pajdla'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 Tomáš Pajdla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomáš Pajdla more than expected).
This network shows the impact of papers produced by Tomáš Pajdla. 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 Tomáš Pajdla. The network helps show where Tomáš Pajdla may publish in the future.
Co-authorship network of co-authors of Tomáš Pajdla
This figure shows the co-authorship network connecting the top 25 collaborators of Tomáš Pajdla.
A scholar is included among the top collaborators of Tomáš Pajdla 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 Tomáš Pajdla. Tomáš Pajdla is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Arrigoni, Federica, Tomáš Pajdla, & Andrea Fusiello. (2023). Viewing Graph Solvability in Practice. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 8113–8121.1 indexed citations
Arrigoni, Federica, Andrea Fusiello, Elisa Ricci, & Tomáš Pajdla. (2021). Viewing Graph Solvability via Cycle Consistency. Institutional Research Information System (University of Udine).7 indexed citations
5.
Toft, Carl, Will Maddern, Akihiko Torii, et al.. (2020). Long-Term Visual Localization Revisited. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(4). 2074–2088.113 indexed citations
Kúkelová, Zuzana, et al.. (2015). R6P - Rolling Shutter Absolute Camera Pose. Computer Vision and Pattern Recognition. 2292–2300.21 indexed citations
8.
Barnes, Robert, Sanjeev Gupta, M. Giordano, et al.. (2015). Geological interpretation and analysis of surface based, spatially referenced planetary imagery data using PRoGIS 2.0 and Pro3D.. elib (German Aerospace Center).2 indexed citations
9.
Paar, Gerhard, Jan‐Peter Müller, Yu Tao, et al.. (2015). PRoViDE: Planetary Robotics Vision Data Processing and Fusion. elib (German Aerospace Center).2 indexed citations
Chum, Ondřej, et al.. (2006). 3d geometry from uncalibrated images.3 indexed citations
18.
Pajdla, Tomáš & Jiřı́ Matas. (2004). Computer vision -- ECCV 2004 : 8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004 : proceedings. Springer eBooks.2 indexed citations
19.
Pajdla, Tomáš, et al.. (2003). On the Epipolar Geometry of the Crossed-Slits Projection. 988–995.7 indexed citations
20.
Benyon, David, Manfred Fahle, Erik Granum, et al.. (2002). An Investigation into Virtual Representation of Real Places.4 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.