activity
20162020
most citedRePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation

9 citations · 20 across the 4 of their papers we have counts for

collaborators

11 papers

cs.GR2020

LSMAT Least Squares Medial Axis Transform

Daniel Rebain, Baptiste Angles, Julien Valentin +4

The medial axis transform has applications in numerous fields including visualization, computer graphics, and computer vision. Unfortunately, traditional medial axis transformation…

eess.IV20205 cited

Deep Implicit Volume Compression

Danhang Tang, Saurabh Singh, Philip A. Chou +11

We describe a novel approach for compressing truncated signed distance fields (TSDF) stored in 3D voxel grids, and their corresponding textures. To compress the TSDF, our method re…

cs.CV20209 cited

RePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation

Hossam Isack, Christian Haene, Cem Keskin +4

We propose a novel efficient and lightweight model for human pose estimation from a single image. Our model is designed to achieve competitive results at a fraction of the number o…

cs.GR20194 cited

VIPER: Volume Invariant Position-based Elastic Rods

Baptiste Angles, Daniel Rebain, Miles Macklin +8

We extend the formulation of position-based rods to include elastic volumetric deformations. We achieve this by introducing an additional degree of freedom per vertex -- isotropic…

cs.CV20192 cited

Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning

Rohit Pandey, Anastasia Tkach, Shuoran Yang +9

Volumetric (4D) performance capture is fundamental for AR/VR content generation. Whereas previous work in 4D performance capture has shown impressive results in studio settings, th…

cs.CV2018

LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering

Ricardo Martin-Brualla, Rohit Pandey, Shuoran Yang +14

Motivated by augmented and virtual reality applications such as telepresence, there has been a recent focus in real-time performance capture of humans under motion. However, given…