Science
Meshcapade takes the scientific understanding of human body
and brings it to you using patented technology.
Want to join our research team? Look at our open positions.
Our Publications
TokenHMR: Advancing Human Mesh Recovery with a Tokenized Pose Representation
CVPR 2024
Other selected publications by Meshcapade scientists
Naureen Mahmood
SMPL: A skinned multi-person linear model
ACM transactions on graphics (TOG) 34 (6), 1-16, 2015
MoSh: Motion and shape capture from sparse markers
ACM Transactions on Graphics (TOG) 33 (6), 1-13, 2014
Dyna: A model of dynamic human shape in motion
ACM Transactions on Graphics (TOG) 34 (4), 1-14, 2015
Muhammed Kocabas
Yu Sun
TRACE: 5D Temporal Regression of Avatars With Dynamic Cameras in 3D Environments
CVPR 2023
Putting People in their Place: Monocular Regression of 3D People in Depth
CVPR 2022
Yan Zhang
Yao Feng
Learning an animatable detailed 3D face model from in-the-wild images
SIGGRAPH 2021
MeshDiffusion: Score-based generative 3D mesh modeling
Capturing and animation of body and clothing from monocular video
Siggraph Asia 2022
Radu Alexandru Rosu
Neural Strands: Learning Hair Geometry and Appearance from Multi-View Images
ECCV 2022
PermutoSDF: Fast Multi-View Reconstruction with Implicit Surfaces using Permutohedral Lattices
CVPR 2023
Nitin Saini
SmartMocap: Joint Estimation of Human and Camera Motion Using Uncalibrated RGB Cameras
IEEE Robotics and Automation Letters, 8(6):3206-3213, 2023
AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation
IEEE Robotics and Automation Letters, 7(2):4805-4812, IEEE, April 2022
AirCapRL: Autonomous Aerial Human Motion Capture Using Deep Reinforcement Learning
IEEE Robotics and Automation Letters, 7(2):4805-4812, IEEE, April 2022
Markerless Outdoor Human Motion Capture Using Multiple Autonomous Micro Aerial Vehicles
ICCV 219
Michael J. Black
Keep it SMPL: Automatic estimation of 3D human pose and shape from a single image
ECCV 2016
Embodied hands: Modeling and capturing hands and bodies together
ACM Transactions on Graphics, (Proc. SIGGRAPH Asia), 36(6):245:1-245:17, 245:1–245:17, ACM, November 2017
Learning a model of facial shape and expression from 4D scans
ACM Trans. Graph. 36 (6), 194:1-194:17, 2017
Recovering accurate 3D human pose in the wild using IMUs and a moving camera
ECCV 2018
Learning to reconstruct 3D human pose and shape via model-fitting in the loop
ICCV 2019
BEDLAM: A synthetic dataset of bodies exhibiting detailed lifelike animated motion
CVPR 2023