COCO-WholeBody — The First Dataset to Evaluate The Whole Body Pose
Published in
2 min readAug 13, 2020
COCO-WholeBody is the first dataset for evaluating whole body posture. COCO-WholeBody is an extension of the COCO 2017 dataset with the same training and validation breakdowns as COCO. There are 4 types of object boundaries available for each person: person box, face box, left-hand box, and right-hand box. In addition, 133 key points: 17 for the body, 6 for the legs, 68 for the face, and 42 for the arms. The dataset is available exclusively for research purposes. Commercial use is prohibited.
How the dataset was collected
The marking process consisted of the following steps:
- For each person, the boundaries of the face, left hand and right hand were manually marked;
- Quality assessment: a separate group of markers checked the quality of the lines;
- For each marked face and hand, a pre-trained model was used to mark key points. HRNetV2 was used as the detector architecture;
- The predicted markup was then manually checked. After that, the quality of manual marking was checked separately.