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BABEL Action Recognition Challenge

 
Evaluation Server: https://babel-evaluation.is.tuebingen.mpg.de/
 
Use the code in action_recognition/challenge/create_submission.py, in our Github repo to create a submission file. 
 
Task
 
Given a motion-capture span of 5 sec. or lesser, predict the likelihood (score) of actions in it. See the BABEL paper for details regarding the task. 
 
See the action_recognition/ folder in our Github repo for reference code for a baseline model. 
 
Challenge settings
 
There are 4 different “Challenge settings” in the action recognition task, with two variables: 
  1. Number of classes
    1. BABEL-60 subset containing spans of mocap sequences belonging to 60 classes. 
    2. BABEL-120 subset containing spans of mocap sequences belonging to 120 classes. 
  1. Type of labels
    1. Dense labels only — the submission uses only the following two files: train.json and val.json for training and validation. 
    2. Dense + Extra labels — the submission uses train.json, val.json, and in addition, extra_train.json and extra_val.json during training and validation. 
  • For details regarding the Dense labels and Extra labels, please visit our Data page. 
 
Predictions
 
Please refer to the action_recognition/challenge folder in the BABEL GitHub repository for details regarding generating a submission file on the test set. 
 
Submit your predictions to our Action Recognition Evaluation Server (Coming Soon). 

 


Acknowledgement

Thanks to the Software Workshop at Max-Planck Institute for Intelligent Systems for developing the BABEL Action Recognition evalation server. 

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