Rehg, James M.

Multiple Hypothesis Tracking Revisited

Kim, C., Li, F., Ciptadi, A., & Rehg, J. M. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 666

Ego4D: Around the World in 3,000 Hours of Egocentric Video

Grauman, K., Westbury, A., Byrne, E., Chavis, Z., Furnari, A., Girdhar, R., Hamburger, J., Jiang, H., Liu, M., Liu, X., et al. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Human Pose and Action RecognitionContext-Aware Activity Recognition Systems

Cited by 630

Learning to recognize objects in egocentric activities

Fathi, A., Ren, X., & Rehg, J. M. (2011) · CVPR 2011

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications

Cited by 557

Understanding egocentric activities

Fathi, A., Farhadi, A., & Rehg, J. M. (2011) · 2011 International Conference on Computer Vision

Context-Aware Activity Recognition SystemsHuman Pose and Action Recognition

Cited by 384

Joint Semantic Segmentation and 3D Reconstruction from Monocular Video

Kundu, A., Li, Y., Dellaert, F., Li, F., & Rehg, J. M. (2014) · Lecture Notes in Computer Science

Advanced Vision and ImagingRobotics and Sensor-Based Localization

Cited by 220

Modeling Actions through State Changes

Fathi, A., & Rehg, J. M. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 145

Learning and inference in parametric switching linear dynamic systems

Oh, S. M., Rehg, J. M., Balch, T., & Dellaert, F. (2005) · Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1

Bayesian Methods and Mixture ModelsControl Systems and Identification

Cited by 40

Mobile Health: Sensors, Analytic Methods, and Applications

Kumar, S., Murphy, S. A., & Rehg, J. M. (2017) · Springer eBooks

Mobile Health and mHealth ApplicationsContext-Aware Activity Recognition Systems

Cited by 38

Parameterized Duration Mmodeling for Switching Linear Dynamic Systems

Oh, S. M., Rehg, J. M., & Dellaert, F. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06)

Control Systems and IdentificationBayesian Methods and Mixture Models

Cited by 26

The mobile assistance for regulating smoking (MARS) micro-randomized trial design protocol

Nahum-Shani, I., Potter, L. N., Lam, C. Y., Yap, J., Moreno, A., Stoffel, R., Wu, Z., Wan, N., Dempsey, W., Kumar, S., et al. (2021) · Contemporary Clinical Trials

Smoking Behavior and CessationMobile Health and mHealth Applications

Cited by 23

Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

Grauman, K., Westbury, A., Torresani, L., Kitani, K., Malik, J., Afouras, T., Ashutosh, K., Baiyya, V., Bansal, S., Boote, B., et al. (2025) · International Journal of Computer Vision

Human Pose and Action RecognitionContext-Aware Activity Recognition Systems

Cited by 3