François Rameau

1.5k total citations · 1 hit paper
29 papers, 743 citations indexed

About

François Rameau is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Media Technology. According to data from OpenAlex, François Rameau has authored 29 papers receiving a total of 743 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 12 papers in Aerospace Engineering and 7 papers in Media Technology. Recurrent topics in François Rameau's work include Advanced Vision and Imaging (16 papers), Robotics and Sensor-Based Localization (12 papers) and Video Surveillance and Tracking Methods (7 papers). François Rameau is often cited by papers focused on Advanced Vision and Imaging (16 papers), Robotics and Sensor-Based Localization (12 papers) and Video Surveillance and Tracking Methods (7 papers). François Rameau collaborates with scholars based in South Korea, United States and Canada. François Rameau's co-authors include In So Kweon, Seokju Lee, Fei Pan, Inkyu Shin, Jean‐Charles Bazin, Junsik Kim, Kyungdon Joo, Chaoning Zhang, Jinsun Park and Philipp Benz and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

François Rameau

28 papers receiving 727 citations

Hit Papers

Unsupervised Intra-Domain Adaptation for Semantic Segment... 2020 2026 2022 2024 2020 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
François Rameau South Korea 13 555 245 142 104 77 29 743
Wei-Chen Chiu Taiwan 16 873 1.6× 242 1.0× 145 1.0× 166 1.6× 77 1.0× 55 1.1k
Guangliang Cheng China 17 731 1.3× 341 1.4× 88 0.6× 159 1.5× 65 0.8× 33 988
Mingyu Ding China 15 682 1.2× 280 1.1× 236 1.7× 54 0.5× 40 0.5× 38 902
Xianxu Hou China 16 646 1.2× 297 1.2× 62 0.4× 108 1.0× 102 1.3× 38 959
Yi‐Hsuan Tsai United States 17 1.2k 2.2× 328 1.3× 114 0.8× 144 1.4× 57 0.7× 41 1.5k
Zhiwu Lu China 15 626 1.1× 358 1.5× 193 1.4× 44 0.4× 46 0.6× 30 839
Seunghoon Hong South Korea 13 967 1.7× 321 1.3× 90 0.6× 71 0.7× 55 0.7× 25 1.2k
Jiachen Li China 11 500 0.9× 179 0.7× 76 0.5× 112 1.1× 35 0.5× 21 694
Hongyang Li China 14 806 1.5× 374 1.5× 126 0.9× 90 0.9× 79 1.0× 25 1.0k
Bowen Cheng United States 8 639 1.2× 220 0.9× 86 0.6× 98 0.9× 53 0.7× 12 855

Countries citing papers authored by François Rameau

Since Specialization
Citations

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

Fields of papers citing papers by François Rameau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of François Rameau

This figure shows the co-authorship network connecting the top 25 collaborators of François Rameau. A scholar is included among the top collaborators of François Rameau 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 François Rameau. François Rameau 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.
Rameau, François, et al.. (2025). InstaGraM: Instance-Level Graph Modeling for Vectorized HD Map Learning. IEEE Transactions on Intelligent Transportation Systems. 26(2). 1889–1899. 1 indexed citations
2.
Rameau, François, et al.. (2024). Multi-Modal Place Recognition via Vectorized HD Maps and Images Fusion for Autonomous Driving. IEEE Robotics and Automation Letters. 9(5). 4710–4717. 4 indexed citations
3.
Rameau, François, et al.. (2023). CCTV-Calib: a toolbox to calibrate surveillance cameras around the globe. Machine Vision and Applications. 34(6). 2 indexed citations
4.
Hold-Geoffroy, Yannick, et al.. (2023). A Perceptual Measure for Deep Single Image Camera and Lens Calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(9). 10603–10614. 6 indexed citations
5.
Rameau, François, et al.. (2022). MC-Calib: A generic and robust calibration toolbox for multi-camera systems. Computer Vision and Image Understanding. 217. 103353–103353. 25 indexed citations
6.
Lee, Seokju, François Rameau, Sunghoon Im, & In So Kweon. (2022). Self-Supervised Monocular Depth and Motion Learning in Dynamic Scenes: Semantic Prior to Rescue. International Journal of Computer Vision. 130(9). 2265–2285. 6 indexed citations
7.
Rameau, François, et al.. (2022). Real-Time Multi-Car Localization and See-Through System. International Journal of Computer Vision. 130(2). 384–404. 3 indexed citations
8.
Zhang, Chaoning, Philipp Benz, Seokju Lee, et al.. (2021). ResNet or DenseNet? Introducing Dense Shortcuts to ResNet. 3549–3558. 99 indexed citations
9.
Lee, Seokju, François Rameau, Fei Pan, & In So Kweon. (2021). Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 4842–4851. 22 indexed citations
10.
Kim, Junsik, et al.. (2021). Optical Flow Estimation from a Single Motion-blurred Image. Proceedings of the AAAI Conference on Artificial Intelligence. 35(2). 891–900. 12 indexed citations
11.
Im, Sunghoon, et al.. (2021). VolumeFusion: Deep Depth Fusion for 3D Scene Reconstruction. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 16066–16075. 1 indexed citations
12.
Pan, Fei, Inkyu Shin, François Rameau, Seokju Lee, & In So Kweon. (2020). Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision. 3763–3772. 248 indexed citations breakdown →
13.
Zhang, Chaoning, François Rameau, Seokju Lee, et al.. (2019). Revisiting Residual Networks with Nonlinear Shortcuts.. British Machine Vision Conference. 12. 13 indexed citations
14.
Rameau, François, et al.. (2019). Latent Question Interpretation Through Variational Adaptation. IEEE/ACM Transactions on Audio Speech and Language Processing. 27(11). 1713–1724. 5 indexed citations
15.
Park, Jinsun, Kyungdon Joo, François Rameau, et al.. (2019). Vehicular Multi-Camera Sensor System for Automated Visual Inspection of Electric Power Distribution Equipment. 281–288. 6 indexed citations
16.
Cho, Donghyeon, YunJae Jung, François Rameau, et al.. (2019). Video Retargeting. 882–889. 3 indexed citations
17.
Joo, Kyungdon, et al.. (2019). Segment2Regress: Monocular 3D Vehicle Localization in Two Stages. 4 indexed citations
18.
Rameau, François, et al.. (2018). Efficient adaptive non-maximal suppression algorithms for homogeneous spatial keypoint distribution. Pattern Recognition Letters. 106. 53–60. 34 indexed citations
20.
Park, Kibaek, Hyowon Ha, François Rameau, & In So Kweon. (2015). Fused robot pose estimation using embedded and external cameras. 375–376.

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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