Masked autoencoder for multiagent trajectories

Automatically labeling trajectories of multiple agents is key to behavioral analyses but usually requires a large amount of manual annotations. This also applies to the domain of team sport analyses. In this paper, we specifically show how pretraining transformer models improves the classification p...

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Bibliographic Details
Published in:	Machine learning Vol. 114; no. 2; p. 44
Main Authors:	Rudolph, Yannick, Brefeld, Ulf
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.02.2025 Springer Nature B.V
Subjects:	Annotations Artificial Intelligence Behavior Classification Computer Science Control Entomology Machine Learning Mechatronics Multiagent systems Natural Language Processing (NLP) Permutations Professional soccer Robotics Simulation and Modeling Soccer Special Issue on Machine Learning in Soccer Transformer Tracking data Masked autoencoder Soccer Multiagent trajectories Self-supervised learning
ISSN:	0885-6125, 1573-0565
Online Access:	Get full text
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