ObMan-Ego
Introduced by Ohkawa et al. in Foreground-Aware Stylization and Consensus Pseudo-Labeling for Domain Adaptation of First-Person Hand Segmentation
The ObMan-Ego is a large-scale synthetic hand dataset with egocentric scenes in which the simulated hands are provided by ObMan. The dataset is used for a hand segmentation task and its sim-to-real adaptation benchmark. Training, validation, and testing sets contain 150, 000, 6, 500, and 6, 500 images, respectively.
Papers
| Paper | Code | Results | Date | Stars |
|---|
Dataset Loaders
No data loaders found. You can
submit your data loader here.
No data loaders found. You can
submit your data loader here.
