The objective of this work is human pose estimation in videos, where multiple frames are
available. We investigate a ConvNet architecture that is able to benefit from temporal context …

The only goal of the abstract is to the answer the question: why should I read this paper? In
this paper we study the use of convolutional neural networks (convnets) for the task of …

Person detection is a key problem for many computer vision tasks. While face detection has
reached maturity, detecting people under full variation of camera view-points, human poses …

We investigate the importance of parts for the tasks of action and attribute classification. We
develop a part-based approach by leveraging convolutional network features inspired by …

In this paper we propose a contextual rescoring method for predicting the position of body
parts in a human pose estimation framework. A set of poselets is incorporated in the model …

Multisensory information processing is a basic feature of neural systems and has been
exploited to facilitate development of Army systems that augment Soldier performance …

Deep methods based on Convolutional Neural Networks serve as accurate facial points and
body parts detectors. However, most methods do not provide a confidence score for the …

Résumé In this thesis, we address person detection and action prediction in visual data. We
develop models that learn representations for visual data and the structure in the output …

In this paper, we propose a novel approach to detect human pose in a wild image. The
approach uses a nonparametric representation, which we refer as DirectionMaps, to learn …

Recent years have seen a continued growth in the amount of information populating
information systems. Meanwhile, the proliferation of computer-based communications and …