Sławomir Bąk
- Computer Vision and Pattern Recognition top 1%
- Automotive Engineering top 1%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Safety, Risk, Reliability and Quality top 2%
- Co-authors
- Peter CarrFrançois BrémondEtienne CorvéePatsorn SangkloyAndrew T. HartnettSimon LuceyJagjeet SinghJames Hays
- Topics
- Video Surveillance and Tracking Methods (12 papers)Human Pose and Action Recognition (8 papers)Gait Recognition and Analysis (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionAutomotive EngineeringSafety, Risk, Reliability and Quality
- Journals
- IEEE Transactions on Circuits and Systems for Video TechnologyIEEE Transactions on Systems Man and Cybernetics SystemsINFORMS journal on computing
- Partner nations
- United StatesFranceItaly
In The Last Decade
Sławomir Bąk
14 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 64
- Computer Vision and Pattern Recognition 984
- Automotive Engineering 577
- Artificial Intelligence 236
- Biomedical Engineering 229
- Safety, Risk, Reliability and Quality 150
Countries citing papers authored by Sławomir Bąk
This map shows the geographic impact of Sławomir Bąk'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 Sławomir Bąk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sławomir Bąk more than expected).
Fields of papers citing papers by Sławomir Bąk
This network shows the impact of papers produced by Sławomir Bąk. 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 Sławomir Bąk. The network helps show where Sławomir Bąk may publish in the future.
Co-authorship network of co-authors of Sławomir Bąk
This figure shows the co-authorship network connecting the top 25 collaborators of Sławomir Bąk. A scholar is included among the top collaborators of Sławomir Bąk 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 Sławomir Bąk. Sławomir Bąk is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Argoverse: 3D Tracking and Forecasting With Rich Mapsbreakdown → | 882 |
| 2 | 2 | |
| 3 | 9 | |
| 4 | 2 | |
| 5 | 93 | |
| 6 | 15 | |
| 7 | 15 | |
| 8 | 10 | |
| 9 | 1 | |
| 10 | 72 | |
| 11 | 161 | |
| 12 | 8 | |
| 13 | 109 | |
| 14 | 4 |
About Sławomir Bąk
Sławomir Bąk is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Biomedical Engineering, having authored 14 papers that have together received 1.4k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (12 papers), Human Pose and Action Recognition (8 papers) and Gait Recognition and Analysis (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (984 citations), Automotive Engineering (577 citations) and Safety, Risk, Reliability and Quality (150 citations). Sławomir Bąk has collaborated with scholars based in United States, France and Italy. Frequent co-authors include Peter Carr, François Brémond, Etienne Corvée, Patsorn Sangkloy, Andrew T. Hartnett, Simon Lucey, Jagjeet Singh, James Hays, Ming-Fang Chang and Deva Ramanan. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Systems Man and Cybernetics Systems and INFORMS journal on computing.
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.