Ben Sapp
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- Advanced Vision and Imaging 2
- Human Pose and Action Recognition 1
- Video Surveillance and Tracking Methods 1
- Multimodal Machine Learning Applications 1
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety 4
- Human-Computer Interaction top 5%
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- Traffic and Road Safety 2
- Artificial Intelligence top 5%
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- Traffic Prediction and Management Techniques 3
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- Time Series Analysis and Forecasting 1
- Co-authors
- Ben TaskarTimothée CourDragomir AnguelovYuning ChaiScott EttingerBenjamin CaineZoey YangAlexander P. McCauley
- Journals
- Journal of Machine Learning Research (1 paper)IEEE Robotics and Automation Letters (1 paper)2022 International Conference on Robotics and Automation (ICRA) (1 paper)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Ben Sapp
6 papers receiving 711 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Computer Vision and Pattern Recognition 438
- Automotive Engineering 250
- Human-Computer Interaction 81
- Safety, Risk, Reliability and Quality 81
- Artificial Intelligence 251
Countries citing papers authored by Ben Sapp
This map shows the geographic impact of Ben Sapp'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 Ben Sapp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Sapp more than expected).
Fields of papers citing papers by Ben Sapp
This network shows the impact of papers produced by Ben Sapp. 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 Ben Sapp. The network helps show where Ben Sapp may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ben Sapp, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2022 | 15 | |
| 3 | 2022 | 48 | |
| 4 | Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Datasetbreakdown → | 2021 | 300 |
| 5 | 2013 | 248 | |
| 6 | Learning from Partial Labels | 2011 | 124 |
| 7 | Language models for semantic extraction and filtering in video action recognition | 2011 | 2 |
About Ben Sapp
Ben Sapp is a scholar working on Automotive Engineering, Building and Construction, Safety, Risk, Reliability and Quality, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 7 papers that have together received 737 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (4 papers), Traffic Prediction and Management Techniques (3 papers), Advanced Vision and Imaging (2 papers), Traffic and Road Safety (2 papers), Human Pose and Action Recognition (1 paper), Video Surveillance and Tracking Methods (1 paper), Time Series Analysis and Forecasting (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (438 citations), Automotive Engineering (250 citations), Human-Computer Interaction (81 citations), Safety, Risk, Reliability and Quality (81 citations) and Artificial Intelligence (251 citations). Ben Sapp has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Ben Taskar, Timothée Cour, Dragomir Anguelov, Yuning Chai, Scott Ettinger, Benjamin Caine, Zoey Yang, Alexander P. McCauley, Chenxi Liu and Jiquan Ngiam. Their work appears in journals such as Journal of Machine Learning Research, IEEE Robotics and Automation Letters, 2022 International Conference on Robotics and Automation (ICRA) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.