Estimating the pose of a human in 3D given an image or a video has recently received
significant attention from the scientific community. The main reasons for this trend are the …

Recent transformer-based solutions have been introduced to estimate 3D human pose from
2D keypoint sequence by considering body joints among all frames globally to learn spatio …

Abstract Model-based 3D pose and shape estimation methods reconstruct a full 3D mesh for
the human body by estimating several parameters. However, learning the abstract …

We study the recent progress on dynamic view synthesis (DVS) from monocular video.
Though existing approaches have demonstrated impressive results, we show a discrepancy …

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 …

In this paper, we study the problem of learning Graph Convolutional Networks (GCNs) for
regression. Current architectures of GCNs are limited to the small receptive field of …

In this work, we propose a method that combines a single hand-held camera and a set of
Inertial Measurement Units (IMUs) attached at the body limbs to estimate accurate 3D poses …

Abstract We describe Human Mesh Recovery (HMR), an end-to-end framework for
reconstructing a full 3D mesh of a human body from a single RGB image. In contrast to most …

This work addresses the problem of estimating the full body 3D human pose and shape from
a single color image. This is a task where iterative optimization-based solutions have …

Direct prediction of 3D body pose and shape remains a challenge even for highly
parameterized deep learning models. Map** from the 2D image space to the prediction …