COCO-WholeBody dataset is the first large-scale benchmark for whole-body pose estimation. It is an extension of COCO 2017 dataset with the same train/val split ... |
COCO-WholeBody is an extension of COCO dataset with whole-body annotations. There are 4 types of bounding boxes (person box, face box, left-hand box, ... |
The current state-of-the-art on COCO-WholeBody is Sapiens-2B. See a full comparison of 16 papers with code. |
COCO-WholeBody annotation contains all the data of COCO keypoint annotation (including keypoints, num_keypoints, etc.) and additional fields. |
... WholeBody Dataset is a large-scale dataset with keypoint and bounding box annotations. As shown in Figure 6, this dataset extended the existing COCO ... |
This is an extension to OpenPifPaf to detect body, foot, face and hand keypoints, which sum up to 133 keypoints per person. |
4 авг. 2020 г. · Для каждого человека доступны 4 типа границ объектов: бокс человека, бокс лица, бокс левой руки и бокс правой руки. Кроме того, ключевые 133 ... |
The model is first pre-trained on original COCO dataset, and then fine-tuned on COCO-WholeBody dataset. We find this will lead to better performance. |
23 июл. 2020 г. · Extensive experiments show that COCO-WholeBody not only can be used to train deep models from scratch for whole-body pose estimation but also ... |
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