1.1k citations · 1.8k across the 21 of their papers we have counts for
27 papers
RHINO: Reconstructing Human Interactions with Novel Objects from Monocular Videos
Lixin Xue, Chengwei Zheng, Georgios Paschalidis +4
Reconstructing people, objects, and their interactions in 3D is a long-standing goal for intelligent systems. Often the input is RGB video from a moving camera, making the task ill…
POCO: 3D Pose and Shape Estimation with Confidence
Sai Kumar Dwivedi, Cordelia Schmid, Hongwei Yi +2
The regression of 3D Human Pose and Shape (HPS) from an image is becoming increasingly accurate. This makes the results useful for downstream tasks like human action recognition or…
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…
Detecting Human-Object Contact in Images
Yixin Chen, Sai Kumar Dwivedi, Michael J. Black +1
Humans constantly contact objects to move and perform tasks. Thus, detecting human-object contact is important for building human-centered artificial intelligence. However, there e…
3D Human Pose Estimation via Intuitive Physics
Shashank Tripathi, Lea Müller, Chun-Hao P. Huang +3
Estimating 3D humans from images often produces implausible bodies that lean, float, or penetrate the floor. Such methods ignore the fact that bodies are typically supported by the…
ECON: Explicit Clothed humans Optimized via Normal integration
Yuliang Xiu, Jinlong Yang, Xu Cao +2
The combination of deep learning, artist-curated scans, and Implicit Functions (IF), is enabling the creation of detailed, clothed, 3D humans from images. However, existing methods…
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…
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…
ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation
Zicong Fan, Omid Taheri, Dimitrios Tzionas +4
Humans intuitively understand that inanimate objects do not move by themselves, but that state changes are typically caused by human manipulation (e.g., the opening of a book). Thi…
Human-Aware Object Placement for Visual Environment Reconstruction
Hongwei Yi, Chun-Hao P. Huang, Dimitrios Tzionas +5
Humans are in constant contact with the world as they move through it and interact with it. This contact is a vital source of information for understanding 3D humans, 3D scenes, an…
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…
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…
ICON: Implicit Clothed humans Obtained from Normals
Yuliang Xiu, Jinlong Yang, Dimitrios Tzionas +1
Current methods for learning realistic and animatable 3D clothed avatars need either posed 3D scans or 2D images with carefully controlled user poses. In contrast, our goal is to l…
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…
Populating 3D Scenes by Learning Human-Scene Interaction
Mohamed Hassan, Partha Ghosh, Joachim Tesch +2
Humans live within a 3D space and constantly interact with it to perform tasks. Such interactions involve physical contact between surfaces that is semantically meaningful. Our goa…
GRAB: A Dataset of Whole-Body Human Grasping of Objects
Omid Taheri, Nima Ghorbani, Michael J. Black +1
Training computers to understand, model, and synthesize human grasping requires a rich dataset containing complex 3D object shapes, detailed contact information, hand pose and shap…
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…
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…
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…
Learning to Train with Synthetic Humans
David T. Hoffmann, Dimitrios Tzionas, Micheal J. Black +1
Neural networks need big annotated datasets for training. However, manual annotation can be too expensive or even unfeasible for certain tasks, like multi-person 2D pose estimation…
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…
Learning joint reconstruction of hands and manipulated objects
Yana Hasson, Gül Varol, Dimitrios Tzionas +4
Estimating hand-object manipulations is essential for interpreting and imitating human actions. Previous work has made significant progress towards reconstruction of hand poses and…
3D Object Reconstruction from Hand-Object Interactions
Dimitrios Tzionas, Juergen Gall
Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches are successful for a wide range of object clas…
Capturing Hand Motion with an RGB-D Sensor, Fusing a Generative Model with Salient Points
Dimitrios Tzionas, Abhilash Srikantha, Pablo Aponte +1
Hand motion capture has been an active research topic in recent years, following the success of full-body pose tracking. Despite similarities, hand tracking proves to be more chall…