192 citations · 223 across the 6 of their papers we have counts for
15 papers
SUPR: A Sparse Unified Part-Based Human Representation
Ahmed A. A. Osman, Timo Bolkart, Dimitrios Tzionas +1
Statistical 3D shape models of the head, hands, and fullbody are widely used in computer vision and graphics. Despite their wide use, we show that existing models of the head and h…
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…
Capturing and Animation of Body and Clothing from Monocular Video
Yao Feng, Jinlong Yang, Marc Pollefeys +2
While recent work has shown progress on extracting clothed 3D human avatars from a single image, video, or a set of 3D scans, several limitations remain. Most methods use a holisti…
EMOCA: Emotion Driven Monocular Face Capture and Animation
Radek Danecek, Michael J. Black, Timo Bolkart
As 3D facial avatars become more widely used for communication, it is critical that they faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3…
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…
Collaborative Regression of Expressive Bodies using Moderation
Yao Feng, Vasileios Choutas, Timo Bolkart +2
Recovering expressive humans from images is essential for understanding human behavior. Methods that estimate 3D bodies, faces, or hands have progressed significantly, yet separate…