The MECCANO dataset is the first dataset of egocentric videos to study human-object interactions in industrial-like settings.
The MECCANO dataset has been acquired in an industrial-like scenario in which subjects built a toy model of a motorbike. We considered 20 object classes which include the 16 classes categorizing the 49 components, the two tools (screwdriver and wrench), the instructions booklet and a partial_model class.
Additional details related to the MECCANO:
20 different subjects in 2 countries (IT, U.K.)
Video Acquisition: 1920x1080 at 12.00 fps
11 training videos and 9 validation/test videos
8857 video segments temporally annotated indicating the verbs which describe the actions performed
64349 active objects annotated with bounding boxes
12 verb classes, 20 objects classes and 61 action classes
Variants: MECCANO
This dataset is used in 3 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Human-Object Interaction Detection | SlowFast + FasterRCNN | The MECCANO Dataset: Understanding Human-Object … | 2020-10-12 |
| Action Recognition | SlowFast | The MECCANO Dataset: Understanding Human-Object … | 2020-10-12 |
| Object Recognition | Faster-RCNN | The MECCANO Dataset: Understanding Human-Object … | 2020-10-12 |
Recent papers with results on this dataset: