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Found 11 papers, 6 papers with code
HMP: Hand Motion Priors for Pose and Shape Estimation from Video
Therefore, we develop a generative motion prior specific for hands, trained on the AMASS dataset which features diverse and high-quality hand motions.
Reconstructing Signing Avatars From Video Using Linguistic Priors
A perceptual study shows that SGNify's 3D reconstructions are significantly more comprehensible and natural than those of previous methods and are on par with the source videos.
Spatio-Temporal Action Detection Under Large Motion
Current methods for spatiotemporal action tube detection often extend a bounding box proposal at a given keyframe into a 3D temporal cuboid and pool features from nearby frames.
Accurate 3D Body Shape Regression using Metric and Semantic Attributes
Since paired data with images and 3D body shape are rare, we exploit two sources of information: (1) we collect internet images of diverse "fashion" models together with a small set of anthropometric measurements; (2) we collect linguistic shape attributes for a wide range of 3D body meshes and the model images.
Ranked #6 on
3D Human Shape Estimation
on SSP-3D
GOAL: Generating 4D Whole-Body Motion for Hand-Object Grasping
This is challenging, as it requires the avatar to walk towards the object with foot-ground contact, orient the head towards it, reach out, and grasp it with a realistic hand pose and hand-object contact.
Learning to Fit Morphable Models
A common first step in systems that tackle these problems is to regress the parameters of the parametric model directly from the input data.
Collaborative Regression of Expressive Bodies using Moderation
Second, human shape is highly correlated with gender, but existing work ignores this.
Monocular Expressive Body Regression through Body-Driven Attention
To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image.
Resolving 3D Human Pose Ambiguities with 3D Scene Constraints
To motivate this, we show that current 3D human pose estimation methods produce results that are not consistent with the 3D scene.
Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
We use the new method, SMPLify-X, to fit SMPL-X to both controlled images and images in the wild.
Ranked #1 on
3D Human Reconstruction
on Expressive hands and faces dataset (EHF)
(TR V2V (mm), left hand metric)
PoTion: Pose MoTion Representation for Action Recognition
We use the human joints as these keypoints and term our Pose moTion representation PoTion.
Ranked #1 on
Skeleton Based Action Recognition
on J-HMDB
