1.1k citations · 1.1k across the 5 of their papers we have counts for
10 papers
Human Body Measurement Estimation with Adversarial Augmentation
Nataniel Ruiz, Miriam Bellver, Timo Bolkart +4
We present a Body Measurement network (BMnet) for estimating 3D anthropomorphic measurements of the human body shape from silhouette images. Training of BMnet is performed on data…
AutoAvatar: Autoregressive Neural Fields for Dynamic Avatar Modeling
Ziqian Bai, Timur Bagautdinov, Javier Romero +3
Neural fields such as implicit surfaces have recently enabled avatar modeling from raw scans without explicit temporal correspondences. In this work, we exploit autoregressive mode…
Embodied Hands: Modeling and Capturing Hands and Bodies Together
Javier Romero, Dimitrios Tzionas, Michael J. Black
Humans move their hands and bodies together to communicate and solve tasks. Capturing and replicating such coordinated activity is critical for virtual characters that behave reali…
Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency
Soubhik Sanyal, Alex Vorobiov, Timo Bolkart +5
Synthesizing images of a person in novel poses from a single image is a highly ambiguous task. Most existing approaches require paired training images; i.e. images of the same pers…
SMPLpix: Neural Avatars from 3D Human Models
Sergey Prokudin, Michael J. Black, Javier Romero
Recent advances in deep generative models have led to an unprecedented level of realism for synthetically generated images of humans. However, one of the remaining fundamental limi…
Learning Multi-Human Optical Flow
Anurag Ranjan, David T. Hoffmann, Dimitrios Tzionas +3
The optical flow of humans is well known to be useful for the analysis of human action. Recent optical flow methods focus on training deep networks to approach the problem. However…