Research Contributions
Our researchers are actively involved in the broader industrial engineering and computer vision research communities. We share some of this technical work here.
We present a Self-Supervised Approach for Training Viewpoint-, Actor-, and Scene-Invariant Video Representations. Our peer-reviewed research was accepted for publication at CVPR 2021

We present a Self-Supervised Approach for Training Viewpoint-, Actor-, and Scene-Invariant Video Representations. Our peer-reviewed research was accepted for publication at CVPR 2021

Video

With this workshop, we bring together computer vision researchers and leaders from academia and industry for exchange of ideas that lie at the intersection of computer vision and the smart factory.
We present a novel framework for unsupervised anomaly detection in video streams, evaluated on dashcam video datasets. Our peer-reviewed research was published at IV 2020.
We present a novel approach for activity recognition in few-shot settings. Our peer-reviewed research was published at the IEEE Transactions on Pattern Analysis and Machine Intelligence 2021.
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