Abstract We present Ego-Exo4D a diverse large-scale multimodal multiview video dataset
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …

Synthesizing semantic-aware, long-horizon, human-object interaction is critical to simulate
realistic human behaviors. In this work, we address the challenging problem of generating …

Modeling human behaviors in contextual environments has a wide range of applications in
character animation, embodied AI, VR/AR, and robotics. In real-world scenarios, humans …

Abstract We propose Diffusion Noise Optimization (DNO) a new method that effectively
leverages existing motion diffusion models as motion priors for a wide range of motion …

We introduce Nymeria-a large-scale, diverse, richly annotated human motion dataset
collected in the wild with multiple multimodal egocentric devices. The dataset comes with a) …

Human and environment sensing are two important topics in Computer Vision and Graphics.
Human motion is often captured by inertial sensors, while the environment is mostly …

While head-mounted devices are becoming more compact they provide egocentric views
with significant self-occlusions of the device user. Hence existing methods often fail to …

What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …

Social interaction is a fundamental aspect of human behavior and communication. The way
individuals position themselves in relation to others also known as proxemics conveys social …

Abstract We present EgoExo-Fitness, a new full-body action understanding dataset,
featuring fitness sequence videos recorded from synchronized egocentric and fixed …