8 citations · 14 across the 8 of their papers we have counts for
12 papers
GNM Head: A Generative aNthropometric Model of the human head
Stylianos Ploumpis, Jan Bednarik, Gaspard Zoss +29
Parametric models of the human head are essential tools traditionally used in computer vision and graphics for animation, rendering, and reconstruction. More recently, they serve a…
BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objects
Wanyue Zhang, Rishabh Dabral, Vladislav Golyanik +5
We present BimArt, a novel generative approach for synthesizing 3D bimanual hand interactions with articulated objects. Unlike prior works, we do not rely on a reference grasp, a c…
Learning to Stabilize Faces
Jan Bednarik, Erroll Wood, Vasileios Choutas +4
Nowadays, it is possible to scan faces and automatically register them with high quality. However, the resulting face meshes often need further processing: we need to stabilize the…
Reconstructing Signing Avatars From Video Using Linguistic Priors
Maria-Paola Forte, Peter Kulits, Chun-Hao Huang +4
Sign language (SL) is the primary method of communication for the 70 million Deaf people around the world. Video dictionaries of isolated signs are a core SL learning tool. Replaci…
Spatio-Temporal Action Detection Under Large Motion
Gurkirt Singh, Vasileios Choutas, Suman Saha +2
Current methods for spatiotemporal action tube detection often extend a bounding box proposal at a given keyframe into a 3D temporal cuboid and pool features from nearby frames. Ho…
Accurate 3D Body Shape Regression using Metric and Semantic Attributes
Vasileios Choutas, Lea Muller, Chun-Hao P. Huang +3
While methods that regress 3D human meshes from images have progressed rapidly, the estimated body shapes often do not capture the true human shape. This is problematic since, for…
GOAL: Generating 4D Whole-Body Motion for Hand-Object Grasping
Omid Taheri, Vasileios Choutas, Michael J. Black +1
Generating digital humans that move realistically has many applications and is widely studied, but existing methods focus on the major limbs of the body, ignoring the hands and hea…
Learning to Fit Morphable Models
Vasileios Choutas, Federica Bogo, Jingjing Shen +1
Fitting parametric models of human bodies, hands or faces to sparse input signals in an accurate, robust, and fast manner has the promise of significantly improving immersion in AR…
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…
Monocular Expressive Body Regression through Body-Driven Attention
Vasileios Choutas, Georgios Pavlakos, Timo Bolkart +2
To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image. Most existing method…
Resolving 3D Human Pose Ambiguities with 3D Scene Constraints
Mohamed Hassan, Vasileios Choutas, Dimitrios Tzionas +1
To understand and analyze human behavior, we need to capture humans moving in, and interacting with, the world. Most existing methods perform 3D human pose estimation without expli…
Expressive Body Capture: 3D Hands, Face, and Body from a Single Image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani +4
To facilitate the analysis of human actions, interactions and emotions, we compute a 3D model of human body pose, hand pose, and facial expression from a single monocular image. To…