Computer vision is undergoing a period of rapid progress, rekindling the relationship between perception, action, and cognition. Such connections may be best practically explored in the context of autonomous robotics. In this talk, I will discuss perceptual understanding tasks motivated by embodied robots "in-the-wild", focusing on the illustrative case of autonomous vehicles. I will argue that many challenges that surface are not well-explored in contemporary computer vision. These include streaming computation with bounded resources, generalization via spatiotemporal grouping, online behavioral forecasting, and self-aware processing that can recognize anomalous out-of-sample data. I will conclude with a description of open challenges for embodied perception in-the-wild.
Deva Ramanan is an associate professor at the Robotics Institute at Carnegie-Mellon University and the director of the CMU Argo AI Center for Autonomous Vehicle Research. Prior to joining CMU, he was an associate professor at UC Irvine. His research interests span computer vision and machine learning, with a focus on visual recognition. He was awarded the David Marr Prize in 2009, the PASCAL VOC Lifetime Achievement Prize in 2010, an NSF Career Award in 2010, the UCI Chancellor's Award for Excellence in Undergraduate Research in 2011, the PAMI Young Researcher Award in 2012, one of Popular Science's Brilliant 10 researchers in 2012, and the Longuet-Higgins Prize in 2018 for fundamental contributions in computer vision. His work is supported by NSF, ONR, DARPA, as well as industrial collaborations with Intel, Google, and Microsoft.
He is on the editorial board of the International Journal of Computer Vision (IJCV) and is an associate editor for the IEEE Transactions onPattern Analysis and Machine Intelligence (PAMI). He regularly serves as a senior program committee member for the IEEE Conference of Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision (ICCV), and the European Conference on Computer Vision (ECCV). He served as program chair of CVPR 2018. He also regularly serves on NSF panels for computer vision and machine learning.