TY  - CONF
AU  - Artur Xarles
AU  - Sergio Escalera
AU  - Thomas B. Moeslund
AU  - Albert Clapes
A2  - MMSports
PY  - 2023//
TI  - ASTRA: An Action Spotting TRAnsformer for Soccer Videos
BT  - Proceedings of the 6th International Workshop on Multimedia Content Analysis in Sports
SP  - 93–102
N2  - In this paper, we introduce ASTRA, a Transformer-based model designed for the task of Action Spotting in soccer matches. ASTRA addresses several challenges inherent in the task and dataset, including the requirement for precise action localization, the presence of a long-tail data distribution, non-visibility in certain actions, and inherent label noise. To do so, ASTRA incorporates (a) a Transformer encoder-decoder architecture to achieve the desired output temporal resolution and to produce precise predictions, (b) a balanced mixup strategy to handle the long-tail distribution of the data, (c) an uncertainty-aware displacement head to capture the label variability, and (d) input audio signal to enhance detection of non-visible actions. Results demonstrate the effectiveness of ASTRA, achieving a tight Average-mAP of 66.82 on the test set. Moreover, in the SoccerNet 2023 Action Spotting challenge, we secure the 3rd position with an Average-mAP of 70.21 on the challenge set.
UR  - https://doi.org/10.1145/3606038.3616153
N1  - HUPBA
ID  - Artur Xarles2023
ER  -