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...
This paper addresses the problem of automatic temporal
annotation of realistic human actions in video using mini-
mal manual supervision. To this end we consider two asso-
ciate...
Olivier Duchenne, Ivan Laptev, Josef Sivic, Franci...
Because of the large variation across different environments, a generic classifier trained on extensive data-sets may perform sub-optimally in a particular test environment. In th...
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
Abstract. Sparse signal models learned from data are widely used in audio, image, and video restoration. They have recently been generalized to discriminative image understanding t...
Julien Mairal, Marius Leordeanu, Francis Bach, Mar...