Search Results for author:
Found 6 papers, 3 papers with code
StylePeople: A Generative Model of Fullbody Human Avatars
We show that with the help of neural textures, such avatars can successfully model clothing and hair, which usually poses a problem for mesh-based approaches.
Real-time RGBD-based Extended Body Pose Estimation
We use parametric 3D deformable human mesh model (SMPL-X) as a representation and focus on the real-time estimation of parameters for the body pose, hands pose and facial expression from Kinect Azure RGB-D camera.
CNN with large memory layers
We have tested the memory layer on the classification, image reconstruction and relocalization problems and found that for some of those, the memory layers can provide significant speed/accuracy improvement with the high utilization of the key-value elements, while others require more careful fine-tuning and suffer from dying keys.
Textured Neural Avatars
In particular, our system estimates an explicit two-dimensional texture map of the model surface.
Learnable Triangulation of Human Pose
We present two novel solutions for multi-view 3D human pose estimation based on new learnable triangulation methods that combine 3D information from multiple 2D views.
Ranked #3 on
3D Human Pose Estimation
on Panoptic
(using extra training data)
Semi-parametric Image Inpainting
This paper introduces a semi-parametric approach to image inpainting for irregular holes.
