Search Results for author:
Found 6 papers, 3 papers with code
HumMUSS: Human Motion Understanding using State Space Models
Understanding human motion from video is essential for a range of applications, including pose estimation, mesh recovery and action recognition.
Speech Driven Tongue Animation
In this work, we introduce a large-scale speech and mocap dataset that focuses on capturing tongue, jaw, and lip motion.
SelfPose: 3D Egocentric Pose Estimation from a Headset Mounted Camera
The quantitative evaluation, on synthetic and real-world datasets, shows that our strategy leads to substantial improvements in accuracy over state of the art egocentric approaches.
xR-EgoPose: Egocentric 3D Human Pose from an HMD Camera
Our quantitative evaluation, both on synthetic and real-world datasets, shows that our strategy leads to substantial improvements in accuracy over state of the art egocentric pose estimation approaches.
Ranked #7 on
Egocentric Pose Estimation
on GlobalEgoMocap Test Dataset
(using extra training data)
Rethinking Pose in 3D: Multi-stage Refinement and Recovery for Markerless Motion Capture
We propose a CNN-based approach for multi-camera markerless motion capture of the human body.
Ranked #211 on
3D Human Pose Estimation
on Human3.6M
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
We propose a unified formulation for the problem of 3D human pose estimation from a single raw RGB image that reasons jointly about 2D joint estimation and 3D pose reconstruction to improve both tasks.
Ranked #22 on
Weakly-supervised 3D Human Pose Estimation
on Human3.6M
