BABEL: Bodies, Action and Behavior with English Labels
2021-06-18
The BABEL dataset consists of labels that describe the action being performed in a mocap sequence. There are two types of labels — sequence labels that describe the actions being performed in the entire sequence, and fine-grained frame labels that describe the actions being performed in each frame. The mocap sequences in BABEL are derived from the AMASS dataset. The GitHub repo consists of helper code that loads and filters the data based on labels. It also consists of training code, features, and pre-trained models that perform the task of action recognition on the BABEL dataset.
| Author(s): | Abhinanda R. Punnakkal and Arjun Chandrasekaran and Nikos Athanasiou and Alejandra Quiros-Ramirez and Michael J. Black |
| Department(s): |
Perceiving Systems |
| Research Projects(s): |
Inferring Actions Language and Movement |
| Publication(s): |
{BABEL}: Bodies, Action and Behavior with English Labels
|
| Authors: | Abhinanda R. Punnakkal and Arjun Chandrasekaran and Nikos Athanasiou and Alejandra Quiros-Ramirez and Michael J. Black |
| Release Date: | 2021-06-18 |
| Repository: | https://github.com/abhinanda-punnakkal/BABEL |
| External Link: | https://babel.is.tue.mpg.de/ |
