Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …

We propose TRAM, a two-stage method to reconstruct a human's global trajectory and
motion from in-the-wild videos. TRAM robustifies SLAM to recover the camera motion in the …

While head-mounted devices are becoming more compact they provide egocentric views
with significant self-occlusions of the device user. Hence existing methods often fail to …

What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …

Egocentric human pose estimation aims to estimate human body poses and develop body
representations from a first-person camera perspective. It has gained vast popularity in …

In this work we explore egocentric whole-body motion capture using a single fisheye camera
which simultaneously estimates human body and hand motion. This task presents significant …

We propose RoHM an approach for robust 3D human motion reconstruction from monocular
RGB (-D) videos in the presence of noise and occlusions. Most previous approaches either …

Understanding the world in first-person view is fundamental in Augmented Reality (AR). This
immersive perspective brings dramatic visual changes and unique challenges compared to …

Monocular egocentric 3D human motion capture is a challenging and actively researched
problem. Existing methods use synchronously operating visual sensors (eg RGB cameras) …

Abstract Human Mesh Recovery (HMR) aims to estimate the 3D human body from 2D
images which is a challenging task due to inherent ambiguities in translating 2D …