HOT3D: Hand and Object Tracking in 3D from Egocentric Multi-View Videos

We introduce HOT3D, a publicly available dataset for egocentric hand and object tracking in 3D. The dataset offers over 833 minutes (3.7M+ images) of recordings that feature 19 subjects interacting with 33 diverse rigid objects. In addition to simple pickup, observe, and put-down actions, the subjec...

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Veröffentlicht in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) S. 7061 - 7071
Hauptverfasser:	Banerjee, Prithviraj, Shkodrani, Sindi, Moulon, Pierre, Hampali, Shreyas, Han, Shangchen, Zhang, Fan, Zhang, Linguang, Fountain, Jade, Miller, Edward, Basol, Selen, Newcombe, Richard, Wang, Robert, Engel, Jakob Julian, Hodan, Tomas
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 10.06.2025
Schlagworte:	3d lifting of in-hand objects 6dof object pose aria Artificial intelligence augmented reality Benchmark testing contextual ai dataset hand tracking hand-object interaction Hands Headphones in-hand object segmentation Object tracking Pose estimation smart glasses Synchronization Three-dimensional displays Training Videos virtual reality
ISSN:	1063-6919
Online-Zugang:	Volltext
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