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Vasileios Choutas

9 accepted papers

2025

BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objects

Wanyue Zhang, Rishabh Dabral, Vladislav Golyanik, Vasileios Choutas, Eduardo Alvarado, Thabo Beeler +2
CVPR 2025poster

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 coarse hand trajectory, or separate modes for grasping and articulating. To achieve this, we first generate distance-base…

Cited by 2Source ↗PDF ↗Scholar ↗
2023

Reconstructing Signing Avatars From Video Using Linguistic Priors

Maria-Paola Forte, Peter Kulits, Chun-Hao P. Huang, Vasileios Choutas, Dimitrios Tzionas, Katherine J. Kuchenbecker +1
CVPR 2023poster

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. Replacing these with 3D avatars can aid learning and enable AR/VR applications, improving access to technology and online media…

Cited by 15Source ↗PDF ↗Scholar ↗
2022

Accurate 3D Body Shape Regression Using Metric and Semantic Attributes

Vasileios Choutas, Lea Müller, Chun-Hao P. Huang, Siyu Tang, Dimitrios Tzionas, Michael J. Black
CVPR 2022oral

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 many applications, accurate body shape is as important as pose. The key reason that body shape accuracy lags pose accura…

Cited by 72PDF ↗code ↗Scholar ↗
2022

GOAL: Generating 4D Whole-Body Motion for Hand-Object Grasping

Omid Taheri, Vasileios Choutas, Michael J. Black, Dimitrios Tzionas
CVPR 2022poster

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 head. Hands have been separately studied, but the focus has been on generating realistic static grasps of objects. To synth…

Cited by 124PDF ↗code ↗Scholar ↗
2020

Monocular Expressive Body Regression through Body-Driven Attention

Vasileios Choutas, Georgios Pavlakos, Timo Bolkart, Dimitrios Tzionas, Michael J. Black
ECCV 2020poster

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 methods focus only on parts of the body. A few recent approaches reconstruct full expressive 3D humans from images using 3D bo…

Cited by 283Source ↗PDF ↗code ↗Scholar ↗
2019

Expressive Body Capture: 3D Hands, Face, and Body From a Single Image

Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed A. A. Osman, Dimitrios Tzionas +1
CVPR 2019oral

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 achieve this, we use thousands of 3D scans to train a new, unified, 3D model of the human body, SMPL-X, that extends SM…

Cited by 2080PDF ↗code ↗Scholar ↗
2019

Resolving 3D Human Pose Ambiguities With 3D Scene Constraints

Mohamed Hassan, Vasileios Choutas, Dimitrios Tzionas, Michael J. Black
ICCV 2019poster

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 explicitly considering the scene. We observe however that the world constrains the body and vice-versa. To motivate this, we…

Cited by 359PDF ↗code ↗Scholar ↗
2018

PoTion: Pose MoTion Representation for Action Recognition

Vasileios Choutas, Philippe Weinzaepfel, Jérôme Revaud, Cordelia Schmid
CVPR 2018poster

Most state-of-the-art methods for action recognition rely on a two-stream architecture that processes appearance and motion independently. In this paper, we claim that considering them jointly offers rich information for action recognition. We introduce a novel representation that gracefully encodes…

Cited by 381Source ↗PDF ↗Scholar ↗