Joel Janai

1.4k total citations · 1 hit paper
5 papers, 449 citations indexed

About

Joel Janai is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Artificial Intelligence. According to data from OpenAlex, Joel Janai has authored 5 papers receiving a total of 449 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 2 papers in Automotive Engineering and 1 paper in Artificial Intelligence. Recurrent topics in Joel Janai's work include Advanced Neural Network Applications (3 papers), Autonomous Vehicle Technology and Safety (2 papers) and Advanced Vision and Imaging (2 papers). Joel Janai is often cited by papers focused on Advanced Neural Network Applications (3 papers), Autonomous Vehicle Technology and Safety (2 papers) and Advanced Vision and Imaging (2 papers). Joel Janai collaborates with scholars based in Germany, Netherlands and Switzerland. Joel Janai's co-authors include Andreas Geiger, Fatma Güney, Aseem Behl, Michael J. Black, Anurag Ranjan, Jonas Wulff and Alexandru Paul Condurache and has published in prestigious journals such as 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

In The Last Decade

Joel Janai

5 papers receiving 438 citations

Hit Papers

Computer Vision for Autonomous Vehicles 2020 2026 2022 2024 2020 100 200 300

Peers

Joel Janai
Aseem Behl Germany
Fatma Güney Türkiye
Jingda Guo United States
Qing Rao Germany
Joel Janai
Citations per year, relative to Joel Janai Joel Janai (= 1×) peers Jinlong Li

Countries citing papers authored by Joel Janai

Since Specialization
Citations

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

Fields of papers citing papers by Joel Janai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joel Janai

This figure shows the co-authorship network connecting the top 25 collaborators of Joel Janai. A scholar is included among the top collaborators of Joel Janai 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 Joel Janai. Joel Janai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
1.
Janai, Joel, et al.. (2024). LaneCPP: Continuous 3D Lane Detection Using Physical Priors. 10639–10648. 9 indexed citations
2.
Condurache, Alexandru Paul, et al.. (2023). 3D-SpLineNet: 3D Traffic Line Detection using Parametric Spline Representations. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 602–611. 6 indexed citations
3.
Janai, Joel, Fatma Güney, Aseem Behl, & Andreas Geiger. (2020). Computer Vision for Autonomous Vehicles. 12(1-3). 1–308. 341 indexed citations breakdown →
4.
Ranjan, Anurag, Joel Janai, Andreas Geiger, & Michael J. Black. (2019). Attacking Optical Flow. 2404–2413. 48 indexed citations
5.
Janai, Joel, Fatma Güney, Jonas Wulff, Michael J. Black, & Andreas Geiger. (2017). Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data. 1406–1416. 45 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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2026