Dear colleagues,
The Wearable Technologies Lab at the University of Sussex is glad to inform you about the seventh SHL Activity Recognition Challenge (http://www.shl-dataset.org/activity-recognition-challenge-2025/).
This follows on our very successful 2018, 2019, 2020, 2021, 2023 and 2024 challenges, participation of more than 130 teams and 300 researchers.
Motivated by the growing interest in foundation models, particularly large language models, this year’s edition will explore their application to transportation mode recognition. The goal is to accurately recognize eight modes of locomotion and transportation (activities) in a user-independent manner. Participants will be required to develop a solution that leverages a recognized and well-established foundation model, such as time series models like TimesNet, Chronos, or even models from other domains including language (GPT, BERT) and vision (Flamingo), among others. The provided dataset includes training, validation, and testing sets. Each submission should implement an algorithmic pipeline that utilizes foundation models to process sensor data, build predictive models, and output the recognized activities.
The participants should also write a technical paper explaining their methods and development process, which will be presented at a special session at the HASCA Workshop at Ubicomp 2025, and included in the adjunct proceedings.
For the full rules, please refer to our website:
The timeline of the challengehttp://www.shl-dataset.org/activity-recognition-challenge-2025/
Registration via email: as soon as possible, but not later than 30.04.2025
Challenge duration: 20.04.2025 – 16.06.2025
Submission deadline: 16.06.2025
HASCA-SHL paper submission: 20.06.2025
HASCA Workshop presentation: TBD
Organizers:
Dr. Lin Wang, Queen Mary University of London (UK)
Prof. Daniel Roggen, University of Sussex (UK)
Dr. Mathias Ciliberto, University of Cambridge (UK)
Prof. Hristijan Gjoreski, Ss. Cyril and Methodius University (MK)
Dr. Kazuya Murao, Ritsumeikan University (JP)
Dr. Tsuyoshi Okita, Kyushu Institute of Technology (JP)
Dr. Paula Lago, Concordia University in Montreal (CA)