Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
—Recently, many object localization models have shown that incorporating contextual cues can greatly improve accuracy over using appearance features alone. Therefore, many of the...
Brian McFee, Carolina Galleguillos, Gert R. G. Lan...
The mobile robot localization problem is decomposed into two stages attitude estimation followed by position estimation. The innovation of our method is the use of a smoother, in ...
Stergios I. Roumeliotis, Gaurav S. Sukhatme, Georg...
Sequence comparison is considered as a cornerstone application in bioinformatics, which forms the basis of many other applications. In particular, pairwise sequence alignment is a...
Ankit Agrawal, Sanchit Misra, Daniel Honbo, Alok N...
We propose an algorithm to improve the quality of depth-maps used for Multi-View Stereo (MVS). Many existing MVS techniques make use of a two stage approach which estimates depth-m...