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Found 5 papers, 2 papers with code
HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World
Building an interactive AI assistant that can perceive, reason, and collaborate with humans in the real world has been a long-standing pursuit in the AI community.
CaSAR: Contact-aware Skeletal Action Recognition
Skeletal Action recognition from an egocentric view is important for applications such as interfaces in AR/VR glasses and human-robot interaction, where the device has limited resources.
Context-Aware Sequence Alignment using 4D Skeletal Augmentation
Temporal alignment of fine-grained human actions in videos is important for numerous applications in computer vision, robotics, and mixed reality.
EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devices
Key to reasoning about interactions is to understand the body pose and motion of the interaction partner from the egocentric view.
H2O: Two Hands Manipulating Objects for First Person Interaction Recognition
To this end, we propose a method to create a unified dataset for egocentric 3D interaction recognition.
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