This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
In this paper, we address the problem of learning an
adaptive appearance model for object tracking. In particular,
a class of tracking techniques called “tracking by detectionâ...
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
We investigate the problem of automatically labelling
faces of characters in TV or movie material with their
names, using only weak supervision from automaticallyaligned
subtitl...