Jim Rehg

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2014
Kundu, A., Y. Li, F. Dellaert, F. Li, and J. J. M. Rehg, Joint Semantic Segmentation and 3D Reconstruction from Monocular Video, , 2014. PDF icon eccv2014.Kundu_.Li_.Dellaert.Li_.Rehg_.printed.pdf (4.53 MB)
Li, Y., X. Hou, C. Koch, J. J. M. Rehg, and A. Yuille, The secrets of salient object segmentation, : CVPR, 2014. PDF icon cvpr2014.Li_.Hou_.Koch_.Rehg_.Yuille.final_.pdf (2.14 MB)
2013
Li, Y., A. Fathi, and J. J. M. Rehg, "Learning to Predict Gaze in Egocentric Video", The IEEE International Conference on Computer Vision (ICCV), December, 2013. PDF icon iccv2013.Li_.Fatih_.Rehg_.final_.pdf (946.59 KB)
Li, F., T. Kim, A. Humayun, D. Tsai, and J. J. M. Rehg, "Video Segmentation by Tracking Many Figure-Ground Segments", IEEE International Conference on Computer Vision, 2013. PDF icon ICCV2013_Segtrack2.pdf (927.62 KB)
Li, F., T. Kim, A. Humayun, D. Tsai, and J. J. M. Rehg, "Video Segmentation by Tracking Many Figure-Ground Segments", The IEEE International Conference on Computer Vision (ICCV), December, 2013. PDF icon iccv2013.Li_.Kim_.Humayun.Tsai_.Rehg_.final_.pdf (927.73 KB)
2012
Wang, L., Y. Li, J. Jia, J. Sun, D. Wipf, and J. J. M. Rehg, "Learning sparse covariance patterns for natural scenes", CVPR, 2012. PDF icon cvpr2012.Wang_.Li_.Rehg_.etal_.printed.pdf (836.71 KB)
Fathi, A., J. K. Hodgins, and J. J. M. Rehg, "Social interactions: A first-person perspective", CVPR, 2012. PDF icon cvpr2012.Fathi_.Hodgins.Rehg_.printed.pdf (1.01 MB)
2011
Fathi, A., M F. Balcan, X. Ren, and J. J. M. Rehg, "Combining Self Training and Active Learning for Video Segmentation", Proceedings of the British Machine Vision Conference: BMVA Press, 2011. PDF icon bmvc2011.Fathi_.Balcan.Ren_.Rehg_.final_.pdf (3.06 MB)
Fathi, A., X. Ren, and J. J. M. Rehg, "Learning to recognize objects in egocentric activities", CVPR, 2011. PDF icon cvpr2011.Fathi_.Ren_.Rehg_.printed.pdf (1.39 MB)
Fathi, A., A. Farhadi, and J. J. M. Rehg, "Understanding egocentric activities", ICCV, 2011. PDF icon iccv2011.Fathi_.Farhadi.Rehg_.final_.pdf (782 KB)
 

Dynamics and Control Systems Lab

at Georgia Institute of Technology

 

The Borg Lab

at Georgia Institute of Technology

 

Robotic Mobility Group

at Massachusetts Institute of Technology

 

Aerospace Robotics and Embedded Systems Laboratory

at Massachusetts Institute of Technology

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About us

We are three research groups from Georgia Tech, the Massachusetts Institute of Technology, and the University of Southern California, collaborating to perform basic research on high-speed autonomous driving.  We are most interested in researching biologically-inspired methods in the realms of both perception and control.

Recent Publications

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Acknowledgment

This work was supported by the Army Research Office under MURI Award W911NF-11-1-0046.