Automatic categorization of videos in a Web-scale unconstrained collection such as YouTube is a challenging task. A key issue is how to build an effective training set in the pres...
Zheshen Wang, Ming Zhao, Yang Song, Sanjiv Kumar, ...
We present a novel approach to inferring 3D volumetric shape of both moving objects and static background from video sequences shot by a moving camera, with the assumption that th...
This paper deals with verification methods based on equivalence relations between labeled transition systems. More precisely, we are concerned by two practical needs: how to effi...
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...