Ben Sapp
Impact in
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
Papers in
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- Autonomous Vehicle Technology and Safety 4
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- Advanced Vision and Imaging 2
- Multimodal Machine Learning Applications 1
- Video Surveillance and Tracking Methods 1
- Co-authors
- Ben Taskar (2 shared papers)Timothée Cour (1 shared paper)Dragomir Anguelov (3 shared papers)Yuning Chai (2 shared papers)Scott Ettinger (3 shared papers)Shuyang Cheng (1 shared paper)Yin Zhou (1 shared paper)Vijay Vasudevan (1 shared paper)
- Journals
- IEEE Robotics and Automation Letters (1 paper)Journal of Machine Learning Research (1 paper)2022 International Conference on Robotics and Automation (ICRA) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Ben Sapp
6 papers receiving 814 citations
Ben Sapp's Hit Papers
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 512
- Automotive Engineering 270
- Human-Computer Interaction 95
- Safety, Risk, Reliability and Quality 82
- Artificial Intelligence 286
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-authors
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 | Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset Hit paper breakdown → | 2021 | 335 |
| 2 | MODEC: Multimodal Decomposable Models for Human Pose Estimation Hit paper breakdown → | 2013 | 291 |
| 3 | Learning from Partial Labels | 2011 | 149 |
| 4 | 2022 | 53 | |
| 5 | 2022 | 16 | |
| 6 | Language models for semantic extraction and filtering in video action recognition | 2011 | 2 |
| 7 | 2024 | 0 |
About Ben Sapp
Ben Sapp is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Building and Construction and Safety, Risk, Reliability and Quality, having authored 7 papers that have together received 846 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (4 papers), Traffic Prediction and Management Techniques (3 papers), Traffic and Road Safety (2 papers), Advanced Vision and Imaging (2 papers), Anomaly Detection Techniques and Applications (1 paper), Machine Learning and Algorithms (1 paper), Multimodal Machine Learning Applications (1 paper) and Video Surveillance and Tracking Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (512 citations), Automotive Engineering (270 citations), Human-Computer Interaction (95 citations), Safety, Risk, Reliability and Quality (82 citations) and Artificial Intelligence (286 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, Shuyang Cheng, Yin Zhou, Vijay Vasudevan, Hang Zhao and Pei Sun. Their work appears in journals such as IEEE Robotics and Automation Letters, Journal of Machine Learning Research, 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.