Publications

Recovering 3D Human-Object Interaction (HOI) from single color images is challenging due to depth ambiguities, occlusions, and the huge …

Predicting the dynamics of interacting objects is essential for both humans and intelligent systems. However, existing approaches are …

Estimating the 3D pose and shape of interacting humans and objects from single in-the-wild images is important for mixed reality and …

Synthesizing 3D whole bodies that realistically grasp objects is useful for animation, mixed reality, and robotics. This is …

The regression of 3D Human Pose and Shape HPS from an image is becoming increasingly accurate. This makes the results useful for …

Hands are dexterous and highly versatile manipulators that are central to how humans interact with objects and their environment. …

Understanding how humans use physical contact to interact with the world is key to enabling human-centric artificial intelligence. …

Sign language (SL) is the primary method of communication for the 70 million Deaf people around the world. Video dictionaries of …

The combination of artist-curated scans, and deep implicit functions (IF), is enabling the creation of detailed, clothed, 3D humans …

Humans constantly contact objects to move and perform tasks. Thus, detecting human-object contact is important for building …

Humans intuitively understand that inanimate objects do not move by themselves, but that state changes are typically caused by human …

Estimating 3D humans from images often produces implausible bodies that lean, float, or penetrate the floor. Such methods ignore the …

Statistical 3D shape models of the head, hands, and fullbody are widely used in computer vision and graphics. Despite their wide use, …

Humans constantly interact with daily objects to accomplish tasks. To understand such interactions, computers need to reconstruct these …

Current methods for learning realistic and animatable 3D clothed avatars need either posed 3D scans or 2D images with carefully …

Humans are in constant contact with the world as they move through it and interact with it. This contact is a vital source of …

Generating digital humans that move realistically has many applications and is widely studied, but existing methods focus on the major …

While methods that regress 3D human meshes from images have progressed rapidly, the estimated body shapes often do not capture the true …

Humans live within a 3D space and constantly interact with it to perform tasks. Such interactions involve physical contact between …

Recovering expressive humans from images is essential for understanding human behavior. Methods that estimate 3D bodies, faces, or …

To understand how people look, interact, or perform tasks,we need to quickly and accurately capture their 3D body, face, and hands …

Training computers to understand, model, and synthesize human grasping requires a rich dataset containing complex 3D object shapes, …

To understand and analyze human behavior, we need to capture humans moving in, and interacting with, the world. Most existing methods …

Neural networks need big annotated datasets for training. However, manual annotation can be too expensive or even unfeasible for …

Estimating hand-object manipulations is essential for interpreting and imitating human actions. Previous work has made significant …

To facilitate the analysis of human actions, interactions and emotions, we compute a 3D model of human body pose, hand pose, and facial …

Although commercial and open-source software exist to reconstruct a static object from a sequence recorded with an RGB-D sensor, there …

Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches …

Hand motion capture has been an active research topic in recent years, following the success of full-body pose tracking. Despite …

Benchmarking methods for 3d hand tracking is still an open problem due to the difficulty of acquiring ground truth data. We introduce a …

Post-amputation sensation often translates to the feeling of severe pain in the missing limb, referred to as phantom limb pain (PLP). A clear and rational treatment regimen is difficult to establish, as long as the underlying pathophysiology is not fully known.

An innovative pain management system, namely Epione, is presented here. Epione deals with three main types of pain, i.e., acute pain, chronic pain, and phantom limb pain. In particular, by using facial expression analysis, Epione forms a dynamic pain meter, which then triggers biofeedback and augmented reality-based destruction scenarios, in an effort to maximize patient’s pain relief.