Search Results for author:
Found 15 papers, 9 papers with code
WorldPose: A World Cup Dataset for Global 3D Human Pose Estimation
We present WorldPose, a novel dataset for advancing research in multi-person global pose estimation in the wild, featuring footage from the 2022 FIFA World Cup.
ReLoo: Reconstructing Humans Dressed in Loose Garments from Monocular Video in the Wild
Our method, ReLoo, overcomes this limitation and reconstructs high-quality 3D models of humans dressed in loose garments from monocular in-the-wild videos.
EgoHDM: An Online Egocentric-Inertial Human Motion Capture, Localization, and Dense Mapping System
EgoHDM is the first human mocap system that offers dense scene mapping in near real-time.
MultiPly: Reconstruction of Multiple People from Monocular Video in the Wild
We present MultiPly, a novel framework to reconstruct multiple people in 3D from monocular in-the-wild videos.
EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild
EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters with global body and camera trajectories for in-the-wild videos.
An Interpretable and Attention-based Method for Gaze Estimation Using Electroencephalography
Eye movements can reveal valuable insights into various aspects of human mental processes, physical well-being, and actions.
Hi4D: 4D Instance Segmentation of Close Human Interaction
We propose Hi4D, a method and dataset for the automatic analysis of physically close human-human interaction under prolonged contact.
X-Avatar: Expressive Human Avatars
Our method models bodies, hands, facial expressions and appearance in a holistic fashion and can be learned from either full 3D scans or RGB-D data.
Ranked #2 on
3D Human Reconstruction
on 4D-DRESS
ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation
In part this is because there exist no datasets with ground-truth 3D annotations for the study of physically consistent and synchronised motion of hands and articulated objects.
EM-POSE: 3D Human Pose Estimation From Sparse Electromagnetic Trackers
To this end, we present a method to estimate SMPL parameters from 6-12 EM sensors.
Convolutional Autoencoders for Human Motion Infilling
At the heart of our approach lies the idea to cast motion infilling as an inpainting problem and to train a convolutional de-noising autoencoder on image-like representations of motion sequences.
A Spatio-temporal Transformer for 3D Human Motion Prediction
We propose a novel Transformer-based architecture for the task of generative modelling of 3D human motion.
Structured Prediction Helps 3D Human Motion Modelling
This is implemented via a hierarchy of small-sized neural networks connected analogously to the kinematic chains in the human body as well as a joint-wise decomposition in the loss function.
Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time
To learn from sufficient data, we synthesize IMU data from motion capture datasets.
