Patrick Labatut

2.5k total citations · 1 hit paper
11 papers, 817 citations indexed

About

Patrick Labatut is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Patrick Labatut has authored 11 papers receiving a total of 817 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 4 papers in Computational Mechanics and 4 papers in Aerospace Engineering. Recurrent topics in Patrick Labatut's work include Advanced Vision and Imaging (7 papers), Robotics and Sensor-Based Localization (4 papers) and 3D Shape Modeling and Analysis (4 papers). Patrick Labatut is often cited by papers focused on Advanced Vision and Imaging (7 papers), Robotics and Sensor-Based Localization (4 papers) and 3D Shape Modeling and Analysis (4 papers). Patrick Labatut collaborates with scholars based in France, Israel and United Kingdom. Patrick Labatut's co-authors include Renaud Keriven, Jean-Philippe Pons, David Novotný, Роман Шаповалов, Jeremy Reizenstein, Philipp Henzler, L. Sbordone, Natalia Neverova, Andrea Vedaldi and Artsiom Sanakoyeu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Computer Graphics Forum and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

In The Last Decade

Patrick Labatut

11 papers receiving 782 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.

Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction

2021 183 citations Jeremy Reizenstein, Роман Шаповалов et al. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Patrick Labatut France	8	581	314	262	255	204	11	817
Wentao Yuan United States	6	419 0.7×	305 1.0×	231 0.9×	127 0.5×	451 2.2×	9	794
Shi-Sheng Huang China	13	407 0.7×	222 0.7×	105 0.4×	295 1.2×	140 0.7×	20	621
Rasmus Ramsbøl Jensen Denmark	4	646 1.1×	198 0.6×	249 1.0×	176 0.7×	188 0.9×	7	775
Qiangeng Xu United States	7	537 0.9×	187 0.6×	232 0.9×	168 0.7×	328 1.6×	7	771
Minh-Khoi Tran Singapore	4	289 0.5×	316 1.0×	124 0.5×	155 0.6×	370 1.8×	6	645
Yan‐Pei Cao China	17	576 1.0×	317 1.0×	422 1.6×	125 0.5×	622 3.0×	57	1.1k
Xianzhi Li China	11	394 0.7×	298 0.9×	307 1.2×	73 0.3×	589 2.9×	21	841
Philipp Jenke Germany	12	415 0.7×	133 0.4×	170 0.6×	120 0.5×	237 1.2×	15	591
Minhyuk Sung South Korea	12	370 0.6×	266 0.8×	206 0.8×	100 0.4×	471 2.3×	31	695
Ji Hou China	4	279 0.5×	250 0.8×	65 0.2×	145 0.6×	310 1.5×	10	495

Countries citing papers authored by Patrick Labatut

Since Specialization

Citations

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

Fields of papers citing papers by Patrick Labatut

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Labatut

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

11 of 11 papers shown

1.

Jose, Cijo, Théo Moutakanni, Timothée Darcet, et al.. (2025). DINOv2 Meets Text: A Unified Framework for Image- and Pixel-Level Vision-Language Alignment. 24905–24916. 1 indexed citations

2.

Шаповалов, Роман, David Novotný, Benjamin Graham, Patrick Labatut, & Andrea Vedaldi. (2021). DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 11709–11719. 3 indexed citations

3.

Neverova, Natalia, Artsiom Sanakoyeu, Patrick Labatut, David Novotný, & Andrea Vedaldi. (2021). Discovering Relationships between Object Categories via Universal Canonical Maps. Oxford University Research Archive (ORA) (University of Oxford). 404–413. 11 indexed citations

4.

Reizenstein, Jeremy, Роман Шаповалов, Philipp Henzler, et al.. (2021). Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 10881–10891. 183 indexed citations breakdown →

5.

Neverova, Natalia, David Novotný, Vasil Khalidov, et al.. (2020). Continuous Surface Embeddings. arXiv (Cornell University). 33. 17258–17270. 2 indexed citations

6.

Labatut, Patrick, et al.. (2011). High Accuracy and Visibility-Consistent Dense Multiview Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(5). 889–901. 197 indexed citations

7.

Keriven, Renaud, et al.. (2009). Towards high-resolution large-scale multi-view stereo. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 165 indexed citations

8.

Labatut, Patrick, et al.. (2009). Towards high-resolution large-scale multi-view stereo. HAL (Le Centre pour la Communication Scientifique Directe). 13 indexed citations

9.

Labatut, Patrick, et al.. (2009). Robust and Efficient Surface Reconstruction From Range Data. Computer Graphics Forum. 28(8). 2275–2290. 104 indexed citations

10.

Labatut, Patrick, Jean-Philippe Pons, & Renaud Keriven. (2007). Efficient Multi-View Reconstruction of Large-Scale Scenes using Interest Points, Delaunay Triangulation and Graph Cuts. 1–8. 126 indexed citations

11.

Labatut, Patrick, Renaud Keriven, & Jean-Philippe Pons. (2006). Fast Level Set Multi-View Stereo on Graphics Hardware. 774–781. 12 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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