This paper addresses the problem of efficiently solving large-scale energy minimization problems encountered in computer vision. We propose an energy-aware method for merging ran...
Taesup Kim, Sebastian Nowozin, Pushmeet Kohli, Cha...
Combining information from the higher level and the lower level has long been recognized as an essential component in holistic image understanding. However, an efficient inferenc...
The deformable part-based model (DPM) proposed by Felzenszwalb et al. has demonstrated state-of-the-art results in object localization. The model offers a high degree of learnt in...
Automatic segmentation using multi-atlas label fusion has been widely applied in medical image analysis. To simplify the label fusion problem, most methods implicitly make a stron...
Hongzhi Wang, Jung Wook Suh, John Pluta, Murat Alt...
We present a novel approach to representing and recognizing composite video events. A composite event is specified by a scenario, which is based on primitive events and their tem...
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...
Content-aware image retargeting has attracted a lot of interests recently. The key and most challenging issue for this task is how to balance the tradeoff between preserving the i...
We are interested in the problem of automatic tracking and identification of players in broadcast sport videos shot with a moving camera from a medium distance. While there are m...
Wei-Lwun Lu, Jo-Anne Ting, Kevin Murphy, Jim Littl...
We present a novel theory for characterizing defocus blurs in multi-perspective cameras such as catadioptric mirrors. Our approach studies how multi-perspective ray geometry trans...