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Found 4 papers, 1 papers with code
EventEgo3D: 3D Human Motion Capture from Egocentric Event Streams
In response to the existing limitations, this paper 1) introduces a new problem, i. e., 3D human motion capture from an egocentric monocular event camera with a fisheye lens, and 2) proposes the first approach to it called EventEgo3D (EE3D).
3D Human Pose Perception from Egocentric Stereo Videos
Hence, existing methods often fail to accurately estimate complex 3D poses from egocentric views.
UnrealEgo: A New Dataset for Robust Egocentric 3D Human Motion Capture
We present UnrealEgo, i. e., a new large-scale naturalistic dataset for egocentric 3D human pose estimation.
Ranked #2 on
Egocentric Pose Estimation
on UnrealEgo
Self-Supervised Learning of Domain Invariant Features for Depth Estimation
Specifically, we extend self-supervised learning from traditional representation learning, which works on images from a single domain, to domain invariant representation learning, which works on images from two different domains by utilizing an image-to-image translation network.
