Multi-Agent Behavior Challenge | CVPR 2021

By  vrv

πŸ’‘ Our friends at Northwestern & Caltech are working to solve an important problem in neuroscience.

How to understand the structure of behavior, its control by the brain, and its dependence on context, experience, and more? 🧠

But, the researchers who are studying behavior (our friends) actually end up spending countless hours just painstakingly annotating videos of animals and their actions - losing important time that they can dedicate to doing more research. πŸ˜”

Which led us to host an interesting...and lucrative challenge on AIcrowd! ✨

Can we use machine learning to defeat this 'Annotation bottleneck' for researchers?

🎯 There are 3 goals for this challenge

  1. To develop methods to classify human-defined behaviors from tracked pose trajectories in a large dataset of videos of socially interacting mice
  2. To fine-tune classifications to different annotator styles
  3. To learn to recognize new behaviors of interest from limited training examples.

πŸ’° These tasks have a total prize pool of $9,000!

Task 1

Classical Classification


Task 2

Style Transfer Task


Task 3

Learning New Behavior



🀯 On top of this, we also have total $10,000 Amazon SageMaker credits for first 50 participants/teams to beat the baseline scores by 5%!

And..not only that, eligible winners will also be invited to speak at the Multi-Agent Behaviour Workshop at CVPR2021! 🎀

Check out the competition here

Written by



You must login before you can post a comment.

You may also like...