EgoISM-HOI
Introduced by Leonardi et al. in Exploiting Multimodal Synthetic Data for Egocentric Human-Object Interaction Detection in an Industrial Scenario
EgoISM-HOI is a new multimodal dataset composed of synthetic and real images of egocentric human-objects interactions in an industrial environment with rich annotations of hands and objects. EgoISM-HOI contains a total of 39,304 RGB images, 23,356 depth maps and instance segmentation masks, 59,860 hand annotations, 237,985 object instances across 19 object categories and 35,416 egocentric human-object interactions.
Papers
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