14 datasets found

The dataset used in this paper for training and testing the legged locomotion system using egocentric vision.

Ego-4D dataset

Epic Kitchens dataset is a dataset for egocentric vision and action recognition.

The dataset contains 40 experiences associated with a sewing machine operation task performed by amateur operators.

EPIC-KITCHENS is a large-scale egocentric video benchmark recorded by 32 participants in their native kitchen environments. Our videos depict non-scripted daily activities: we...

The VQ2D dataset is a subset of the Ego4D dataset, containing ground truth tracking annotations for the query object's last appearance.

The EgoLoc dataset is a reformulation of the VQ3D task and a modular pipeline that leads to significant improvements on the Ego4D VQ3D benchmark.

The EGTEA+ dataset contains 28 hours of videos with 106 action categories, with a focus on action recognition.

The ANACTO task is a combination of two tasks merged into one: (1) identifying NAO from past observed segment, and (2) modeling the motion of a person to estimate NAO's location...

Epic-tent: an egocentric video dataset for camping tent assembly

Real-time hand tracking under occlusion from an egocentric RGB-D sensor.

The EGTEA Gaze+ dataset offers approximately 10,000 samples of 106 non-scripted daily activities that occur in a kitchen.

EPIC-KITCHENS-55 is a dataset of 432 videos acquired by 32 subjects and labeled with 39,595 action segments.

Egocentric action anticipation is the task of predicting the future actions a camera wearer will likely perform based on past video observations.