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 …

Estimation of the human pose from a monocular camera has been an emerging research
topic in the computer vision community with many applications. Recently, benefiting from the …

Metaverse as the latest buzzword has attracted great attention from both industry and
academia. Metaverse seamlessly integrates the real world with the virtual world and allows …

We show, for the first time, that neural networks trained only on synthetic data achieve state-
of-the-art accuracy on the problem of 3D human pose and shape (HPS) estimation from real …

The challenging task of multi-object tracking (MOT) requires simultaneous reasoning about
track initialization, identity, and spatio-temporal trajectories. We formulate this task as a …

Tracking by detection, the dominant approach for online multi-object tracking, alternates
between localization and association steps. As a result, it strongly depends on the quality of …

Vision-based monocular human pose estimation, as one of the most fundamental and
challenging problems in computer vision, aims to obtain posture of the human body from …

Human movement is goal-directed and influenced by the spatial layout of the objects in the
scene. To plan future human motion, it is crucial to perceive the environment–imagine how …

Multi-object tracking is a fundamental vision problem that has been studied for a long time.
As deep learning brings excellent performances to object detection algorithms, Tracking by …

Deep learning-based methods for video pedestrian detection and tracking require large
volumes of training data to achieve good performance. However, data acquisition in …