265 citations · 785 across the 88 of their papers we have counts for
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Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time
Yinghao Huang, Manuel Kaufmann, Emre Aksan +3
We demonstrate a novel deep neural network capable of reconstructing human full body pose in real-time from 6 Inertial Measurement Units (IMUs) worn on the user's body. In doing so…
LiveCap: Real-time Human Performance Capture from Monocular Video
Marc Habermann, Weipeng Xu, Michael Zollhoefer +2
We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from…
Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation
Mohamed Omran, Christoph Lassner, Gerard Pons-Moll +2
Direct prediction of 3D body pose and shape remains a challenge even for highly parameterized deep learning models. Mapping from the 2D image space to the prediction space is diffi…
Detailed Human Avatars from Monocular Video
Thiemo Alldieck, Marcus Magnor, Weipeng Xu +2
We present a novel method for high detail-preserving human avatar creation from monocular video. A parameterized body model is refined and optimized to maximally resemble subjects…
Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources
Hosnieh Sattar, Gerard Pons-Moll, Mario Fritz
To study the correlation between clothing garments and body shape, we collected a new dataset (Fashion Takes Shape), which includes images of users with clothing category annotatio…
DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor
Tao Yu, Zerong Zheng, Kaiwen Guo +5
We propose DoubleFusion, a new real-time system that combines volumetric dynamic reconstruction with data-driven template fitting to simultaneously reconstruct detailed geometry, n…
Video Based Reconstruction of 3D People Models
Thiemo Alldieck, Marcus Magnor, Weipeng Xu +2
This paper describes how to obtain accurate 3D body models and texture of arbitrary people from a single, monocular video in which a person is moving. Based on a parametric body mo…