265 citations · 785 across the 88 of their papers we have counts for
10 papers · 1 filter
360-Degree Textures of People in Clothing from a Single Image
Verica Lazova, Eldar Insafutdinov, Gerard Pons-Moll
In this paper we predict a full 3D avatar of a person from a single image. We infer texture and geometry in the UV-space of the SMPL model using an image-to-image translation metho…
Multi-Garment Net: Learning to Dress 3D People from Images
Bharat Lal Bhatnagar, Garvita Tiwari, Christian Theobalt +1
We present Multi-Garment Network (MGN), a method to predict body shape and clothing, layered on top of the SMPL model from a few frames (1-8) of a video. Several experiments demons…
Learning to Dress 3D People in Generative Clothing
Qianli Ma, Jinlong Yang, Anurag Ranjan +4
Three-dimensional human body models are widely used in the analysis of human pose and motion. Existing models, however, are learned from minimally-clothed 3D scans and thus do not…
XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller +7
We present a real-time approach for multi-person 3D motion capture at over 30 fps using a single RGB camera. It operates successfully in generic scenes which may contain occlusions…
Body Shape Privacy in Images: Understanding Privacy and Preventing Automatic Shape Extraction
Hosnieh Sattar, Katharina Krombholz, Gerard Pons-Moll +1
Modern approaches to pose and body shape estimation have recently achieved strong performance even under challenging real-world conditions. Even from a single image of a clothed pe…
Learning to Reconstruct People in Clothing from a Single RGB Camera
Thiemo Alldieck, Marcus Magnor, Bharat Lal Bhatnagar +2
We present a learning-based model to infer the personalized 3D shape of people from a few frames (1-8) of a monocular video in which the person is moving, in less than 10 seconds w…
In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations
Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta +2
Convolutional Neural Network based approaches for monocular 3D human pose estimation usually require a large amount of training images with 3D pose annotations. While it is feasibl…
AMASS: Archive of Motion Capture as Surface Shapes
Naureen Mahmood, Nima Ghorbani, Nikolaus F. Troje +2
Large datasets are the cornerstone of recent advances in computer vision using deep learning. In contrast, existing human motion capture (mocap) datasets are small and the motions…
Tex2Shape: Detailed Full Human Body Geometry From a Single Image
Thiemo Alldieck, Gerard Pons-Moll, Christian Theobalt +1
We present a simple yet effective method to infer detailed full human body shape from only a single photograph. Our model can infer full-body shape including face, hair, and clothi…
SimulCap : Single-View Human Performance Capture with Cloth Simulation
Tao Yu, Zerong Zheng, Yuan Zhong +4
This paper proposes a new method for live free-viewpoint human performance capture with dynamic details (e.g., cloth wrinkles) using a single RGBD camera. Our main contributions ar…