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 …

Kinematic analysis is often performed in a lab using optical cameras combined with
reflective markers. With the advent of artificial intelligence techniques such as deep neural …

Motion capture from sparse inertial sensors has shown great potential compared to image-
based approaches since occlusions do not lead to a reduced tracking quality and the …

Despite the great progress in 3D human pose estimation from videos, it is still an open
problem to take full advantage of a redundant 2D pose sequence to learn representative …

In this work, we demonstrate that 3D poses in video can be effectively estimated with a fully
convolutional model based on dilated temporal convolutions over 2D keypoints. We also …

Comprehensive descriptions of animal behavior require precise three-dimensional (3D)
measurements of whole-body movements. Although two-dimensional approaches can track …

We present two novel solutions for multi-view 3D human pose estimation based on new
learnable triangulation methods that combine 3D information from multiple 2D views. The …

We present an approach to recover absolute 3D human poses from multi-view images by
incorporating multi-view geometric priors in our model. It consists of two separate steps:(1) …

A common approach to localize 3D human joints in a synchronized and calibrated multi-
view setup consists of two-steps:(1) apply a 2D detector separately on each view to localize …

We present a lightweight solution to recover 3D pose from multi-view images captured with
spatially calibrated cameras. Building upon recent advances in interpretable representation …