Abstract Three-dimensional (3D) human pose estimation involves estimating the articulated
3D joint locations of a human body from an image or video. Due to its widespread …

Deep learning approaches have recently raised the bar in many fields, from Natural
Language Processing to Computer Vision, by leveraging large amounts of data. However …

We present the first real-time method to capture the full global 3D skeletal pose of a human
in a stable, temporally consistent manner using a single RGB camera. Our method combines …

We propose a novel attention-based framework for 3D human pose estimation from a
monocular video. Despite the general success of end-to-end deep learning paradigms, our …

Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …

We introduce a new dataset, Human3. 6M, of 3.6 Million accurate 3D Human poses,
acquired by recording the performance of 5 female and 6 male subjects, under 4 different …

We introduce and tackle the problem of zero-shot object detection (ZSD), which aims to
detect object classes which are not observed during training. We work with a challenging set …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

Vision-based human action and activity recognition has an increasing importance among
the computer vision community with applications to visual surveillance, video retrieval and …

In this paper we demonstrate an effective method for parsing clothing in fashion
photographs, an extremely challenging problem due to the large number of possible …