Skip to Main Content
Pro Clubs & Colleges

Predicting Fine-Grained Adversarial Multi-Agent Motion

By: Stats Perform

Our team members Panna Felson, Sujoy Ganguly, and Patrick Lucey’s presented our paper “Where Will They Go? Predicting Fine-Grained Adversarial Multi-Agent Motion using Conditional Variational Autoencoders” at the 2018 European Conference on Computer Vision.

In our paper, we presented a technique using conditional variational auto-encoder which learns a model that “personalises” prediction to individual agent behaviour within a group representation. Given the volume of data available and its adversarial nature, we focused on the sport of basketball to show that our approach efficiently predicts context-specific agent motions. We found that our model generates results that are three times as accurate as previous state-of-the-art approaches (5.74 ft vs. 17.95 ft).

Complete the form and download the full report.