This paper presents a solution to the problem of pose estimation
in the presence of heavy radial distortion and a potentially
large number of outliers. The main contribution is
...
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm...
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...
A major shortcoming of discriminative recognition and detection methods is their noise sensitivity, both during training and recognition. This may lead to very sensitive and britt...