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Found 4 papers, 2 papers with code
EgoPoseFormer: A Simple Baseline for Stereo Egocentric 3D Human Pose Estimation
We also show that our method can be seamlessly extended to monocular settings, which achieves state-of-the-art performance on the SceneEgo dataset, improving MPJPE by 25. 5mm (21% improvement) compared to the best existing method with only 60. 7% model parameters and 36. 4% FLOPs.
Ranked #1 on
Egocentric Pose Estimation
on UnrealEgo
Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning
The key insight is to leverage previously seen "calibration" images of a given user to extrapolate what should be rendered in a novel viewpoint from the data available in the sensor.
LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering
We take the novel approach to augment such real-time performance capture systems with a deep architecture that takes a rendering from an arbitrary viewpoint, and jointly performs completion, super resolution, and denoising of the imagery in real-time.
Low-Dimensionality Calibration Through Local Anisotropic Scaling for Robust Hand Model Personalization
We present a robust algorithm for personalizing a sphere-mesh tracking model to a user from a collection of depth measurements.
